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While these metrics effectively quantify how closely predictions match the ground truth, they do not assess whether model outputs respect predefined logical or domain-specific constraints. In high-stakes applications, including healthcare, finance, and autonomous systems, logical consistency can be as critical as predictive accuracy, yet no standard metric captures this dimension. We introduce the Rule Violation Score (RVS), a complementary evaluation metric that quantifies the extent to which a predictive model respects a given set of logical rules, independently of predictive accuracy. RVS treats hard rules (strict constraints) and soft rules (statistical regularities) differently, can be evaluated on any dataset and on any predictive model expressed over a relational vocabula","title":"Beyond Accuracy: Measuring Logical Compliance of Predictive Models","url":"https://arxiv.org/abs/2606.20208","vendor":"arxiv_cs_ai"},"summary":"arXiv:2606.20208v1 Announce Type: new \nAbstract: Machine learning models are predominantly evaluated through predictive performance metrics such as ranking quality, prediction error, or classification accuracy. While these metrics effectively quantify how closely predictions match the ground truth, they do not assess whether model outputs respect predefined logical or domain-specific constraints. In high-stakes applications, including healthcare, finance, and autonomous systems, logical consistency can be as critical as predictive accuracy, yet no standard metric captures this dimension. We introduce the Rule Violation Score (RVS), a complementary evaluation metric that quantifies the extent to which a predictive model respects a given set of logical rules, independently of predictive accuracy. RVS treats hard rules (strict constraints) and soft rules (statistical regularities) differently, can be evaluated on any dataset and on any predictive model expressed over a relational vocabula","title":"Beyond Accuracy: Measuring Logical Compliance of Predictive Models","vendor":"arxiv_cs_ai"},"confidence":{"method":"deterministic"},"decision":"POSITIVE","issued_at":"2026-06-19T04:43:39Z","notes":"Spider vendor_press (news) news.vendor_press.v1","object":{"captured_by":"crovia.spider.vendor_press","primary_source_url":"https://arxiv.org/abs/2606.20208"},"predecessors":[],"schema":"crovia.axiom.v1","signature":"ed25519:798da4dd07a29f82385084c01ab79ce2cbf46817ebca0efc2851b4a770df520566b6a64b7a23a321b0d47b224a8ad8ac2016d87007874cf3a396f0e0fde05d02","signer":"crovia.substrate","subject":{"observed_at":"2026-06-19T04:43:39Z","source_collector":"spider:vendor_press","target_id":"https://arxiv.org/abs/2606.20208"},"tsa":{"authority":"crovia.substrate.bootstrap","rfc3161_token":"{\"kind\":\"crovia.bootstrap.tsa\",\"source_jsonl\":\"/opt/crovia/spider/data/news/vendor_press_v1.jsonl\",\"source_seal_merkle_root\":\"spider_vendor_press_v1\",\"upgrade_path\":\"Sessione H \\u2014 OpenTimestamps weekly anchor\"}"},"zk_mode":"clear","zk_proof":null},"ledger":{"leaf_hash":"360480ad50cffc5f1df5f7f205aef1daa249b0f83ad86278dc380d43d1ac1f83","leaf_index":235508,"ledger_path":"/opt/crovia/substrate/axiom_ledger.jsonl"},"merkle_proof":{"hash_alg":"sha256","leaf_prefix":"0x00","node_prefix":"0x01","odd_leaf_rule":"duplicate_last","path":[{"sibling":"9833c7d18a88e92f2628fb92fe2daceafd041119a6b2c8a02b4fc39c6f49fae1","side":"right"},{"sibling":"8b4ef5bebe4608969f48884f124e1c73f7b23fa6ccf4294773b20bad4cd95896","side":"right"},{"sibling":"23c1f71e692ba660b65c957d522f2a9db710f954e27d7f29a0c07e505de3cd49","side":"left"},{"sibling":"a4b88936b1283f387366fa1fd86a7b71aee15ebb9763cd37f00db6622e1f7fca","side":"right"},{"sibling":"a3ac6063a401de8c3ccad1f956c4abb3ff631101239ebb518dd4865bc94ef205","side":"left"},{"sibling":"9d5b3a47759460fa8b5eceb45de221aafbf0cd60d3ee412f3351ff44394e520f","side":"left"},{"sibling":"696ac6bcf68966ee959b35539f0bed60b3216ccb53620defd29feb8dbcb2ac30","side":"left"},{"sibling":"95ba45f2fea2d822bc863962b7e478ea50086827d90fab88c0da065d454d7ac5","side":"left"},{"sibling":"00f27f149ddd2eb0d2cf60eaed9e1d55c662cf1cf69c95fbea03bba9d35f90c7","side":"left"},{"sibling":"797e0feb6bf826a55956c876711cd24824818c5a84a591f8cc06b95577b3405d","side":"left"},{"sibling":"f049d6e86b410f6f63921a6e3aa684efffa398fd23eed28245c43b156d404c5f","side":"left"},{"sibling":"9ec7f4f84de7e2057a02ac55686567b21acfd5beaecc7a84e9e48f3db17296c2","side":"right"},{"sibling":"410c633928fea11c5b4bdddb431956b1d7c320db9cda00d2fe32e0fcf888d7b7","side":"left"},{"sibling":"b52a771530dd1686bca49e42088898b86da94879579cd6a995c6ab0598a665fe","side":"right"},{"sibling":"a116bb92f9b0350491155b470acc86d006c33ec558759e49e56614a54c39f242","side":"right"},{"sibling":"a04392fb9f2a3a620840e3b3fecd93d12e6d224e481c162389d8ae64e7194599","side":"left"},{"sibling":"c300cf0154c136afc09b1702a0be98f4ba5b6dc5cf57e8cc714ec1eaf4196eff","side":"left"},{"sibling":"d841ad93efda0869e5eb97678f348f03f5caab4353e05ff4bf18f47fb945b822","side":"left"}]},"schema":"crovia.axiom_proof.v1","seal":{"first_collector_run_id":"","first_receipt_hash":"","jsonl_path":"/opt/crovia/substrate/axiom_ledger.jsonl","key_id":"430895f101d38164","last_collector_run_id":"","last_receipt_hash":"","leaf_count":241122,"merkle_root":"7a906c6a26ff6c6feabc2feaba6a1a70c515e6fd72a38c779293b0f78ff291c4","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","run_id":"hourly_json_retrofit_20260622T183701Z","schema":"crovia.seal.v1","seal_family_version":"crovia-seal-family/1","seal_kind":"substrate_batch","sealed_at":"2026-06-23T06:25:25Z","sig_algorithm":"ed25519","signature":"5576b1d56d5dbb0d96c780fa3ca0940d805c8de95c6251bc87297f0be058aa5e37eb53a6aa1b601381f489f093842cf674b28737ed8e46ce3a49814b5e57290c","signer_version":"1.1.0"},"trust_root":{"key_id":"430895f101d38164","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","signature_algorithm":"ed25519","url":"/registry/canon/TRUST_ROOT.md"},"verifier":{"spec":"/registry/canon/AXIOM_RECEIPT_v1.md","url":"/v/axm_12474d22291f9fe53b3b86bc38e62fa14bdcee280da2ae9992c096c6eb8a6842"}}