{"id":"W4411660132","doi":"10.51847/h24nbtt4r2","title":"10.51847/H24nBtT4R2","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Breast cancer; Medicine; Cancer; Radiology; Oncology; Internal medicine","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":[0.0007057273,0.001341966,0.00101207,0.001249731,0.001154066,0.002241444,0.00168944,0.003674612,0.9476436],"category_scores_gemma":[0.0008604824,0.0003876488,0.0008353422,0.001382214,0.0006758264,0.00141392,0.001570009,0.001276991,0.9567133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001032274,"about_ca_system_score_gemma":0.000812552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002282452,"about_ca_topic_score_gemma":0.002316079,"domain_scores_codex":[0.9995031,0.00004108655,0.0000400124,0.000147124,0.0001794011,0.000089161],"domain_scores_gemma":[0.9992331,0.00008576924,0.00007788002,0.00008428633,0.0001690767,0.000349928],"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":[0.000383505,0.0002254773,0.001419871,0.0003920619,0.00002301541,0.0007246585,0.00005848927,0.0003370698,0.004656752,0.001861072,0.4007532,0.5891649],"study_design_scores_gemma":[0.00007294874,0.00008084546,0.001189628,0.0001377371,0.000009940998,0.0006005558,0.00004534548,0.0001970855,0.0008879327,0.0006700633,0.9960915,0.00001636463],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003764832,0.003236024,0.002043348,0.004202293,0.004309697,0.0002763235,0.004696429,0.002667243,0.9748037],"genre_scores_gemma":[0.003472299,0.0005308294,0.0006943299,0.0007266633,0.0004635625,0.00008385524,0.001243962,0.0001939639,0.9925905],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05235642,"threshold_uncertainty_score":0.07468009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005227906670962044,"score_gpt":0.2248031216310054,"score_spread":0.2195752149600434,"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."}}