{"id":"W163887238","doi":"","title":"Cost-sensitive test strategies","year":2006,"lang":"en","type":"article","venue":"","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Decision tree; Test (biology); Machine learning; Medical costs; Artificial intelligence; Process (computing); Total cost; Test case; Health care","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007569605,0.002141544,0.001596932,0.002274487,0.0005363487,0.001815584,0.002772958,0.002347606,0.002650716],"category_scores_gemma":[0.0358675,0.0005871562,0.0007351884,0.001576512,0.001108804,0.003869023,0.00152455,0.001640153,0.0006086389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001355581,"about_ca_system_score_gemma":0.001553812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001498547,"about_ca_topic_score_gemma":0.001116263,"domain_scores_codex":[0.9935346,0.003133674,0.0004597595,0.0007167142,0.001811704,0.0003435486],"domain_scores_gemma":[0.9743333,0.02018416,0.001507863,0.001522725,0.002101831,0.0003501259],"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":[0.0008689562,0.0007626778,0.01185114,0.0004074395,0.0002296728,0.0005197282,0.0002388506,0.3861825,0.005066989,0.05823437,0.00614794,0.5294898],"study_design_scores_gemma":[0.00012761,0.0004157237,0.001679557,0.00006745286,0.00009450908,0.000514645,0.0001019669,0.914528,0.005174548,0.07418722,0.003056275,0.0000525944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07163121,0.002089937,0.9170871,0.001929202,0.0001271589,0.0009389483,0.0002571369,0.0007895841,0.005149688],"genre_scores_gemma":[0.7004591,0.0006509383,0.2950171,0.0008244344,0.0001133706,0.0005979085,0.0003331731,0.0000853513,0.001918533],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007569605,"threshold_uncertainty_score":0.04003239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02429855596432006,"score_gpt":0.2748367644207455,"score_spread":0.2505382084564254,"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."}}