{"id":"W4375867650","doi":"10.1117/12.2663835","title":"Optimal thermomic biomarkers for early diagnosis of breast cancer","year":2023,"lang":"en","type":"article","venue":"","topic":"Infrared Thermography in Medicine","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Breast cancer; Mammography; Computer science; Breast cancer screening; Artificial intelligence; Pattern recognition (psychology); Cancer; Medicine; Internal medicine","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":[0.0007420919,0.0006856089,0.0006000623,0.001194949,0.0001512225,0.0005789108,0.0003782879,0.0006511513,0.001599446],"category_scores_gemma":[0.002761102,0.0002313301,0.0005368574,0.0005985367,0.0002255937,0.0007133734,0.0004690773,0.0006675523,0.001072055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004086757,"about_ca_system_score_gemma":0.0005047704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001640609,"about_ca_topic_score_gemma":0.00241164,"domain_scores_codex":[0.9996643,0.0001018393,0.00001906597,0.00008433629,0.00007729441,0.00005306478],"domain_scores_gemma":[0.9996091,0.0001455664,0.00008059775,0.0000306827,0.0001070105,0.00002713439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001117922,0.0003064397,0.02953325,0.0004731047,0.0001465755,0.0002256465,0.0001559173,0.07709434,0.1119266,0.00346199,0.01091349,0.7646447],"study_design_scores_gemma":[0.00004075851,0.0003878828,0.02526788,0.0001839286,0.0001677778,0.0005247233,0.0001411034,0.9014853,0.04909745,0.01140317,0.01121087,0.00008923941],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2604186,0.01509836,0.7130761,0.002168584,0.0003641857,0.0001756756,0.001689709,0.002479511,0.004529343],"genre_scores_gemma":[0.8393148,0.00341049,0.1520224,0.0003246239,0.0002296683,0.0001285406,0.001602298,0.0001236468,0.002843669],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001640609,"threshold_uncertainty_score":0.005350709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01750839185823669,"score_gpt":0.2996627809458522,"score_spread":0.2821543890876156,"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."}}