{"id":"W1512585278","doi":"10.1002/sam.11261","title":"Prediction using hierarchical data: Applications for automated detection of cervical cancer","year":2015,"lang":"en","type":"article","venue":"Statistical Analysis and Data Mining The ASA Data Science Journal","topic":"AI in cancer detection","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre","funders":"National Cancer Institute; National Institutes of Health","keywords":"Computer science; Papanicolaou stain; Cervical cancer; Artificial intelligence; Data mining; Pattern recognition (psychology); Machine learning; Cancer; 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":[0.004841551,0.001027248,0.001024126,0.003149082,0.0005670919,0.0009972237,0.001164626,0.00104187,0.001789666],"category_scores_gemma":[0.02213804,0.0004804485,0.001115019,0.003257327,0.0004920029,0.001157065,0.001274913,0.001453169,0.0006736703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0010202,"about_ca_system_score_gemma":0.001386191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01951181,"about_ca_topic_score_gemma":0.02120725,"domain_scores_codex":[0.997725,0.001080657,0.0001835734,0.0003771631,0.0005235133,0.0001101014],"domain_scores_gemma":[0.986356,0.01031658,0.0007876122,0.001209525,0.001050384,0.0002799168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005043037,0.0004925677,0.07304504,0.0003808522,0.0003258676,0.0003498711,0.0003814745,0.3978992,0.003692244,0.006086726,0.01013125,0.5067106],"study_design_scores_gemma":[0.00003016998,0.00005613331,0.004954003,0.00002563432,0.00002190018,0.00004235137,0.00006237686,0.98011,0.001098615,0.01191244,0.001666978,0.00001933178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.115064,0.002567228,0.8645193,0.002704868,0.0002009435,0.000365541,0.005395527,0.007099777,0.002082736],"genre_scores_gemma":[0.6137854,0.0008244109,0.3792456,0.000315732,0.0001757129,0.0003035215,0.004283417,0.0001335397,0.0009327017],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01951181,"threshold_uncertainty_score":0.03879648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1807557257664896,"score_gpt":0.4095357243360112,"score_spread":0.2287799985695216,"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."}}