{"id":"W325298687","doi":"","title":"Image Analysis in Support of Computer-Assisted Cervical Cancer Screening","year":2013,"lang":"en","type":"article","venue":"KTH Publication Database DiVA (KTH Royal Institute of Technology)","topic":"AI in cancer detection","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cervical cancer; Medicine; Population; Quarter (Canadian coin); Cancer; Disease; Environmental health; Geography; Pathology; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004100006,0.0002324727,0.0005117656,0.002438333,0.00008902144,0.00009542685,0.001987878,0.0002400106,0.0002751046],"category_scores_gemma":[0.000162272,0.0002385152,0.0001343394,0.006348919,0.0004022686,0.002026743,0.001096097,0.0003659921,0.00002603046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001540942,"about_ca_system_score_gemma":0.0002092465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003209756,"about_ca_topic_score_gemma":0.0006604889,"domain_scores_codex":[0.9974512,0.00004730941,0.0009066686,0.000750269,0.0004544548,0.0003901374],"domain_scores_gemma":[0.9966218,0.00003618071,0.0006616326,0.001750075,0.0008209622,0.0001093146],"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":[0.00005419786,0.001544595,0.1727308,0.0004724712,0.00130352,0.00002996252,0.0002650159,0.006122032,0.01392015,0.04853858,0.05098482,0.7040339],"study_design_scores_gemma":[0.001668618,0.0002395558,0.2119215,0.0001335603,0.0002344918,0.00001489113,0.00005106994,0.7155176,0.02367233,0.000408081,0.0453797,0.0007586069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05750084,0.00007997003,0.9281806,0.01178678,0.0003736035,0.0005286233,0.000202262,0.0004692514,0.0008780925],"genre_scores_gemma":[0.5682344,0.00002912364,0.4307655,0.0002720119,0.00004151938,0.0002650782,0.0003135212,0.00001331729,0.00006553832],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7093956,"threshold_uncertainty_score":0.9726369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02223391184587433,"score_gpt":0.2804927783751217,"score_spread":0.2582588665292474,"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."}}