{"id":"W4299355318","doi":"10.1136/bmj.321.7263.760","title":"Screening and litigation","year":2000,"lang":"en","type":"article","venue":"BMJ","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kensington Health","funders":"","keywords":"Computer science; Data science; Medicine; World Wide Web; Information retrieval","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":[0.01794453,0.0004157335,0.001042232,0.003778858,0.008415158,0.009847498,0.00161734,0.02812481,0.03433555],"category_scores_gemma":[0.1286374,0.0005685104,0.0009185716,0.002290815,0.01010652,0.006253989,0.005071082,0.01385168,0.003901381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006111686,"about_ca_system_score_gemma":0.01202536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0262193,"about_ca_topic_score_gemma":0.03033979,"domain_scores_codex":[0.976765,0.009393383,0.001154546,0.00207016,0.006636815,0.003980232],"domain_scores_gemma":[0.9574997,0.02661934,0.002566037,0.002853136,0.005902669,0.004559057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000616152,0.00008718969,0.004195723,0.0001142215,0.00003796947,0.0008272725,0.001224035,0.0001815263,0.0001073865,0.6565601,0.2854422,0.05116072],"study_design_scores_gemma":[0.00009361871,0.00009090051,0.009106386,0.001236785,0.00007521299,0.00250174,0.001947257,0.0006851144,0.000225958,0.5856846,0.3982677,0.00008484599],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.008785333,0.01960702,0.002741533,0.5498112,0.004268072,0.00009531174,0.0003742361,0.00008337294,0.4142339],"genre_scores_gemma":[0.4516751,0.01282383,0.002334524,0.3387989,0.01394579,0.0003069065,0.0003708503,0.000113705,0.1796303],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03433555,"threshold_uncertainty_score":0.1148639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3858916672986519,"score_gpt":0.4492152563870715,"score_spread":0.06332358908841962,"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."}}