{"id":"W2122411895","doi":"10.1609/aimag.v25i1.1749","title":"Applications of case-based reasoning in molecular biology","year":2004,"lang":"en","type":"article","venue":"AI Magazine","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Toronto","funders":"","keywords":"Scientific reasoning; Domain (mathematical analysis); Computer science; Case-based reasoning; Artificial intelligence; Management science; Model-based reasoning; Data science; Knowledge representation and reasoning; Engineering; Mathematics education; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002122343,0.00007481052,0.0001137494,0.0001338203,0.00003716993,0.0000146437,0.000263772,0.00005086146,0.000005480718],"category_scores_gemma":[0.00002592547,0.00007545968,0.00002864098,0.0004841816,0.00003278548,0.00006785512,0.00004942534,0.0001142004,0.00002920425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002503813,"about_ca_system_score_gemma":0.0001006669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001698225,"about_ca_topic_score_gemma":0.0000321404,"domain_scores_codex":[0.9993526,0.00003603304,0.0001736645,0.00021004,0.00005841663,0.0001692544],"domain_scores_gemma":[0.9994468,0.00006213198,0.00006383796,0.0003430935,0.00004536875,0.00003875501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001807025,0.0003407574,0.02007607,0.0001305485,0.00003418823,0.001839502,0.0009208363,0.1178475,0.05146089,0.745779,0.0005233517,0.06102927],"study_design_scores_gemma":[0.01189047,0.001782504,0.006706347,0.001265806,0.00008787492,0.002630892,0.00008459417,0.4138101,0.1764887,0.3125209,0.07015797,0.002573835],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01098257,0.0002638164,0.9860968,0.001462922,0.00002520857,0.0001118606,0.000003465743,0.00006353907,0.0009898091],"genre_scores_gemma":[0.7888493,9.851641e-7,0.2105904,0.0005000014,0.000008762851,0.00002403762,0.00000807819,0.000004555801,0.00001395307],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7778667,"threshold_uncertainty_score":0.3077157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007530868579034015,"score_gpt":0.2666576103586232,"score_spread":0.2591267417795892,"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."}}