{"id":"W2058959360","doi":"10.1038/nrc2466","title":"Can genes for mammographic density inform cancer aetiology?","year":2008,"lang":"en","type":"review","venue":"Nature reviews. Cancer","topic":"AI in cancer detection","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Cancer Foundation","funders":"National Cancer Institute","keywords":"Breast cancer; Gene; MAMMOGRAPHIC DENSITY; Genetic predisposition; Cancer; Biology; Bioinformatics; Stromal cell; Genetics; Medicine; Cancer research; Mammography","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":[0.002704881,0.001035626,0.002144983,0.00269481,0.0003009324,0.001353618,0.001711015,0.00240869,0.004432763],"category_scores_gemma":[0.007954177,0.0004624215,0.0008822128,0.002817889,0.001406943,0.001580682,0.0006052895,0.002175631,0.002750942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00109037,"about_ca_system_score_gemma":0.001145674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003669544,"about_ca_topic_score_gemma":0.003656536,"domain_scores_codex":[0.9993857,0.000232186,0.00005619362,0.0001178036,0.0001779707,0.00003008797],"domain_scores_gemma":[0.9932771,0.005333934,0.0002888665,0.0001457525,0.0008580308,0.00009630467],"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":[0.0001306443,0.00004380069,0.002560686,0.00512486,0.0003644352,0.0002004976,0.00006788637,0.0006200913,0.0007004049,0.008945778,0.04950251,0.9317383],"study_design_scores_gemma":[0.0001099592,0.0001659475,0.0144373,0.01410458,0.001028632,0.00368184,0.0003159253,0.001556223,0.0015883,0.06721906,0.8956657,0.0001265016],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002044001,0.9935197,0.0009944523,0.003759337,0.0003719988,0.000005877851,0.00009737189,0.00002142085,0.001025339],"genre_scores_gemma":[0.00320919,0.9937559,0.0009528244,0.0009443858,0.0005300074,0.00001504493,0.000100582,0.000004775608,0.0004872851],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004432763,"threshold_uncertainty_score":0.0148291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0557732485331422,"score_gpt":0.3803880188994403,"score_spread":0.3246147703662982,"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."}}