{"id":"W2908410696","doi":"10.29122/jstmc.v14i1.2680","title":"MENGULAS PENYEBAB BANJIR DI WILAYAH DKI JAKARTA DARI SUDUT PANDANG GEOLOGI, GEOMORFOLOGI DAN MORFOMETRI SUNGAI","year":2013,"lang":"id","type":"article","venue":"Jurnal Sains & Teknologi Modifikasi Cuaca","topic":"Multimedia Learning Systems","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Geography; Flood myth; Cartography; Forestry; Archaeology","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":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.004428482,0.002465315,0.002997974,0.002024276,0.002333237,0.002593334,0.008301673,0.002472811,0.0007273805],"category_scores_gemma":[0.004757981,0.002175211,0.001216693,0.00364141,0.001870549,0.002739465,0.003931649,0.006079996,0.006067148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001493984,"about_ca_system_score_gemma":0.001089019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004659594,"about_ca_topic_score_gemma":0.0004253762,"domain_scores_codex":[0.9810992,0.003831003,0.003319923,0.004071557,0.002628083,0.005050271],"domain_scores_gemma":[0.9868393,0.002833319,0.002525126,0.004688303,0.001359887,0.001754079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003866804,0.004108099,0.6811,0.0008302675,0.002954858,0.003522766,0.01449876,0.01242498,0.02518355,0.006323678,0.05117737,0.197489],"study_design_scores_gemma":[0.005460371,0.00351877,0.516996,0.0006509411,0.0004133931,0.001586245,0.001890568,0.396322,0.003484958,0.000575837,0.0644481,0.004652824],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9555402,0.006491859,0.01280741,0.006286363,0.00747459,0.003664901,0.00007840238,0.001992199,0.005664086],"genre_scores_gemma":[0.9821876,0.0007696035,0.004999083,0.001005995,0.00193048,0.0004407278,0.0001435456,0.0002417278,0.008281193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3838971,"threshold_uncertainty_score":0.9989656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02431599027969329,"score_gpt":0.2512308823036845,"score_spread":0.2269148920239912,"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."}}