{"id":"W2908186035","doi":"10.29122/jstmc.v14i2.2685","title":"USULAN PEMANFAATAN TEKNOLOGI MODIFIKASI CUACA DENGAN GROUND-BASED GENERATOR UNTUK MENAMBAH DEBIT ALIRAN SUNGAI MAMASA, SULAWESI","year":2013,"lang":"id","type":"article","venue":"Jurnal Sains & Teknologi Modifikasi Cuaca","topic":"Coastal Management and Development","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Forestry; Physics; Environmental science; Geography","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","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.002063068,0.002697172,0.002133207,0.0009913616,0.0026844,0.00174251,0.003961813,0.001566079,0.006422366],"category_scores_gemma":[0.0004178581,0.00248253,0.001037242,0.002100483,0.001907024,0.001965684,0.003092273,0.002913946,0.007479211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003340601,"about_ca_system_score_gemma":0.0003906171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005827897,"about_ca_topic_score_gemma":0.004632551,"domain_scores_codex":[0.9851151,0.001467365,0.002871328,0.00362438,0.002389272,0.004532525],"domain_scores_gemma":[0.9933107,0.0004926291,0.001397246,0.002792907,0.0002750881,0.001731467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002060693,0.01090334,0.3925956,0.001309658,0.003649963,0.00435066,0.004933433,0.02309055,0.2317399,0.007513024,0.1095761,0.2082771],"study_design_scores_gemma":[0.01116955,0.003676471,0.656941,0.0005900098,0.001169358,0.0004034066,0.004195726,0.1896565,0.02495726,0.004023449,0.0937323,0.009484956],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9715801,0.002083629,0.002848523,0.005417196,0.002020728,0.004252341,0.0001926058,0.00101485,0.01059],"genre_scores_gemma":[0.9756461,0.0008766699,0.005727171,0.003515386,0.0007399579,0.0006158222,0.0003471858,0.000338788,0.01219296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2643455,"threshold_uncertainty_score":0.9997301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01934250220242222,"score_gpt":0.2254893766552769,"score_spread":0.2061468744528547,"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."}}