{"id":"W3176447062","doi":"10.1609/aaai.v35i11.17161","title":"Interpretable Sequence Classification via Discrete Optimization","year":2021,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Schwartz/Reisman Emergency Medicine Institute; Vector Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada; Canadian Institute for Advanced Research; Agencia Nacional de Investigación y Desarrollo; Microsoft Research","keywords":"Computer science; Artificial intelligence; Sequence (biology); Automaton; Machine learning; TRACE (psycholinguistics); Class (philosophy); Task (project management); Pattern recognition (psychology)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001527015,0.0009769868,0.001079943,0.0008330215,0.0003590699,0.001335097,0.001103255,0.001512878,0.003294763],"category_scores_gemma":[0.008426808,0.0004638105,0.0008582065,0.0005760808,0.001401094,0.001991886,0.001195792,0.00245858,0.0007137157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001500683,"about_ca_system_score_gemma":0.001333689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003133736,"about_ca_topic_score_gemma":0.003488969,"domain_scores_codex":[0.999057,0.0002876231,0.00007036218,0.0003363463,0.0001676244,0.00008104763],"domain_scores_gemma":[0.9949233,0.003998362,0.0002983197,0.0002810542,0.0004035488,0.00009551307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001063926,0.00006909815,0.001103542,0.0001261843,0.00004049964,0.00009880669,0.0001236763,0.8435202,0.001824421,0.02453029,0.001987834,0.1264691],"study_design_scores_gemma":[0.000004179218,0.00001195729,0.00003717018,0.000005968644,0.000002354196,0.00000579675,0.000004756757,0.9850121,0.0002547741,0.01449944,0.000159151,0.000002412854],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02226169,0.0003693199,0.9732711,0.0007854198,0.00006641512,0.00006298296,0.000168256,0.001152123,0.001862622],"genre_scores_gemma":[0.7679281,0.0003283235,0.2254576,0.0005472822,0.0001317239,0.0003901882,0.000788885,0.0002744145,0.004153443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003294763,"threshold_uncertainty_score":0.01102209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03444280696846177,"score_gpt":0.318180685123089,"score_spread":0.2837378781546273,"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."}}