{"id":"W3145943903","doi":"","title":"Analisis Laju Infiltrasi Berbagai Penggunaan Lahan di Desa Kaligending, Karangsambung, Jawa Tengah","year":2021,"lang":"en","type":"article","venue":"Indonesian Mining and Energy Journal","topic":"Water and Land Management","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Physics; Forestry; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003256996,0.0002073972,0.0002225594,0.00008722997,0.0004852102,0.000252179,0.0001943425,0.00008414031,0.0007337772],"category_scores_gemma":[0.00001844159,0.0001731405,0.000099147,0.0002417647,0.00009358187,0.0002693262,0.0001831498,0.0001753015,0.00001365906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006863478,"about_ca_system_score_gemma":0.0000192038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003416683,"about_ca_topic_score_gemma":0.0004387973,"domain_scores_codex":[0.9984664,0.0001293052,0.0003015052,0.0003182188,0.0003319252,0.0004526296],"domain_scores_gemma":[0.9993374,0.00003335841,0.0001115757,0.0001895697,0.00001476464,0.0003133854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004456939,0.000186031,0.8102676,0.00002190969,0.0002263452,0.001751585,0.003679447,0.001626416,0.004855953,0.0006637545,0.02054104,0.1561354],"study_design_scores_gemma":[0.002129028,0.0002544488,0.6780594,0.0001838683,0.0002233573,0.003585589,0.006761016,0.0007813056,0.01022344,0.0004804373,0.2962404,0.001077657],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9619454,0.0003713042,0.001621924,0.0005901844,0.0003250483,0.00001982545,0.000003534823,0.00003402586,0.0350888],"genre_scores_gemma":[0.9954453,0.0003808448,0.0009989367,0.0005337194,0.0002393415,0.000005076894,0.00001268749,0.00002287253,0.002361197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2756994,"threshold_uncertainty_score":0.8034346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007705636050553003,"score_gpt":0.2002104014394994,"score_spread":0.1925047653889464,"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."}}