{"id":"W4383197976","doi":"10.1016/j.ypmed.2023.107605","title":"Development and validation of LightGBM algorithm for optimizing of Helicobacter pylori antibody during the minimum living guarantee crowd based gastric cancer screening program in Taizhou, China","year":2023,"lang":"en","type":"article","venue":"Preventive Medicine","topic":"Helicobacter pylori-related gastroenterology studies","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Medical Science and Technology Project of Zhejiang Province","keywords":"Medicine; Helicobacter pylori; Algorithm; Cancer; Asymptomatic; Internal medicine; Logistic regression; Gastroenterology; Oncology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001035425,0.0002648185,0.0006955769,0.0005472378,0.0001223461,0.000006246956,0.0001239252,0.0000868545,0.0000169848],"category_scores_gemma":[0.000352035,0.0001852332,0.00007972472,0.0008359709,0.0002588973,0.00009503363,0.0001318665,0.0002494231,6.359429e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007727003,"about_ca_system_score_gemma":0.00007116672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000755554,"about_ca_topic_score_gemma":0.00002507476,"domain_scores_codex":[0.9978869,0.0001164078,0.0008154339,0.0003831963,0.0003318662,0.0004662196],"domain_scores_gemma":[0.9988077,0.0002913151,0.00038345,0.0002047738,0.0002499235,0.00006289406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006572907,0.00049454,0.7378597,0.001546139,0.001408492,0.00003855173,0.01544382,0.0002237411,0.09169482,0.000003971746,0.00008167347,0.1505473],"study_design_scores_gemma":[0.004734242,0.0007912518,0.9475751,0.004855232,0.0003478512,0.00001308803,0.001459122,0.007913107,0.03201744,0.000005650773,0.0001453865,0.0001425385],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861709,0.0006360869,0.009838569,0.001396923,0.0001726683,0.001684992,0.00001644574,0.00006536538,0.0000180295],"genre_scores_gemma":[0.9740788,0.000352059,0.0246464,0.00005201081,0.0001519942,0.000472664,0.00007088864,0.00004064507,0.0001345519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2097154,"threshold_uncertainty_score":0.7553593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02335863277608861,"score_gpt":0.3156795343668832,"score_spread":0.2923209015907946,"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."}}