{"id":"W4406479500","doi":"10.1016/s0029-7437(11)70092-1","title":"10.1016/s0029-7437(11)70092-1","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"AI in cancer detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Mammography; Medical physics; Medicine; Internal medicine; Breast cancer; Cancer","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00151528,0.003688405,0.002516126,0.003827519,0.002777307,0.004938524,0.004332115,0.006472094,0.9881327],"category_scores_gemma":[0.002084292,0.001176233,0.001837743,0.003807416,0.002802218,0.006487113,0.003440719,0.003561805,0.9921475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001528873,"about_ca_system_score_gemma":0.001540376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00450755,"about_ca_topic_score_gemma":0.003343746,"domain_scores_codex":[0.9989432,0.0000785341,0.00008436398,0.0003928024,0.0002667966,0.0002344886],"domain_scores_gemma":[0.9971249,0.0009098252,0.0001888929,0.0003354987,0.0005170679,0.000923859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004349971,0.0002593551,0.0009633572,0.0008572183,0.00005994438,0.000331649,0.0001274366,0.0007407409,0.003064457,0.007534395,0.3262607,0.6593658],"study_design_scores_gemma":[0.00005972772,0.0001505304,0.0007281185,0.0004055293,0.00001938929,0.0003755076,0.0001341431,0.0004996705,0.0006317045,0.0008704226,0.9960914,0.00003378484],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0005634327,0.0006510784,0.001499784,0.0004555454,0.0004351457,0.0001451722,0.001264249,0.0011449,0.9938406],"genre_scores_gemma":[0.0007564878,0.0003056124,0.000761784,0.0002083732,0.00008945011,0.00009182908,0.0006949573,0.000231333,0.99686],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01186734,"threshold_uncertainty_score":0.0169273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006994802473245633,"score_gpt":0.1832181926118393,"score_spread":0.1762233901385937,"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."}}