{"id":"W7165839929","doi":"10.53437/j4n1gz59","title":"Monotonicity restored: more never means purer","year":2019,"lang":"","type":"article","venue":"","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Concordia University","funders":"","keywords":"Monotonic function; Measure (data warehouse); Constraint (computer-aided design); Range (aeronautics); Ring (chemistry)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001478628,0.0009293729,0.001045933,0.0003009157,0.000316714,0.0008543219,0.004447551,0.0005433384,0.003703585],"category_scores_gemma":[0.000160132,0.0008550427,0.0006109608,0.001607469,0.0004117416,0.002525293,0.003872852,0.001046104,0.00465342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006273324,"about_ca_system_score_gemma":0.0007142035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000944021,"about_ca_topic_score_gemma":0.00009014752,"domain_scores_codex":[0.9919877,0.0004523135,0.001199291,0.002925615,0.001719576,0.00171547],"domain_scores_gemma":[0.9929911,0.0004549303,0.0003475516,0.004905402,0.0006186715,0.0006823004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002172499,0.003991027,0.08924891,0.0005357765,0.0005946908,0.0003209262,0.0143872,0.04226711,0.001104032,0.2409445,0.02788134,0.5785072],"study_design_scores_gemma":[0.00109794,0.0004807345,0.06271078,0.00004764729,0.00003726349,0.00005917299,0.0001415643,0.8753074,0.000772168,0.007338235,0.0508057,0.001201332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3513172,0.0007689536,0.5836521,0.01490626,0.009856912,0.002844788,0.00002066123,0.0009139979,0.0357191],"genre_scores_gemma":[0.887235,0.00005682225,0.0927322,0.003953803,0.0005416273,0.00003400885,0.000004741245,0.00005699448,0.01538478],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8330404,"threshold_uncertainty_score":0.99939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01545954550353201,"score_gpt":0.2497631386118488,"score_spread":0.2343035931083168,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}