{"id":"W2990357513","doi":"10.14740/gr1210","title":"Diagnosis of Liver Neoplasms by Computational and Statistical Image Analysis","year":2019,"lang":"en","type":"article","venue":"Gastroenterology Research","topic":"AI in cancer detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Hepatocellular carcinoma; Medicine; Nuclear medicine; H&E stain; Pattern recognition (psychology); Pathology; Artificial intelligence; Internal medicine; Computer science; Staining","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006751507,0.00007284531,0.0002022984,0.0003518118,0.00005888577,0.00004504407,0.0003698924,0.0000484612,0.0001801321],"category_scores_gemma":[0.00004512618,0.00007194521,0.00003853189,0.0004905107,0.0003065216,0.0001863028,0.0003621505,0.0002404357,0.00005337018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004611797,"about_ca_system_score_gemma":0.00003032024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000153904,"about_ca_topic_score_gemma":0.00006359469,"domain_scores_codex":[0.9982646,0.0003827504,0.0001848566,0.0003859753,0.0004374699,0.000344395],"domain_scores_gemma":[0.9987826,0.0005972717,0.00005055038,0.0002718417,0.0002091549,0.00008860454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009238185,0.00008361145,0.9880146,0.00002688549,0.0001965066,0.000008723593,0.0001512871,0.0004614984,0.0004801574,0.001461219,0.005246942,0.003776227],"study_design_scores_gemma":[0.0005493859,0.000758222,0.8011721,0.000005461002,0.0000271125,0.00001985731,0.00001920339,0.1951225,0.0003833405,0.001751429,0.0001367791,0.00005453611],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6193733,0.00003762531,0.3799249,0.0004196237,0.00003809014,0.00009969184,0.00002955349,0.00001375453,0.00006346115],"genre_scores_gemma":[0.9686983,0.00003448101,0.03109002,0.00007533105,0.00001030028,0.00002927781,0.00001251287,0.000004602685,0.00004514226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3493251,"threshold_uncertainty_score":0.293384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01829251492289608,"score_gpt":0.3185760461565273,"score_spread":0.3002835312336312,"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."}}