{"id":"W4381621732","doi":"10.31315/psb.v4i1.8874","title":"Analisis Particulate Matter 10 µm (PM10) yang Ditimbulkan oleh Kegiatan Penambangan Andesit di Kabupaten Kulon Progo, DIY","year":2023,"lang":"id","type":"article","venue":"Prosiding Seminar Nasional Teknik Lingkungan Kebumian SATU BUMI","topic":"Computer Science and Engineering","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008145301,0.001034584,0.000882392,0.001904639,0.001364018,0.002380323,0.00052371,0.001023831,0.01021509],"category_scores_gemma":[0.0009735688,0.0005443214,0.001127034,0.001505534,0.0005995678,0.0009064357,0.0008042066,0.001444957,0.002853391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006530788,"about_ca_system_score_gemma":0.001279247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008960903,"about_ca_topic_score_gemma":0.02079872,"domain_scores_codex":[0.9989837,0.000152262,0.0000928199,0.000253275,0.0003660586,0.0001519562],"domain_scores_gemma":[0.9992926,0.0001187371,0.0001293426,0.00005234322,0.0003401065,0.00006682279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002826522,0.00164612,0.5105544,0.006294717,0.00128893,0.005205684,0.00907604,0.0008358194,0.2215188,0.002718815,0.01930461,0.2187296],"study_design_scores_gemma":[0.0001277908,0.002834142,0.6863385,0.00123723,0.001197558,0.006327708,0.0192682,0.001908467,0.1158976,0.003055817,0.1615539,0.0002530921],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9023351,0.01726087,0.01286696,0.001571003,0.0008171824,0.001462063,0.01144908,0.000471397,0.05176634],"genre_scores_gemma":[0.8535253,0.01079035,0.02351899,0.001857364,0.0002441491,0.00146154,0.008192075,0.0002458721,0.1001643],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01021509,"threshold_uncertainty_score":0.03417283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02267505621187665,"score_gpt":0.250458851424866,"score_spread":0.2277837952129894,"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."}}