{"id":"W4399691647","doi":"10.30996/ep.v21i01.9086","title":"Analisa Sebaran Oksigen Terlarut Dan Korelasinya Dengan Suhu Permukaan Laut Menggunakan Citra Landsat-8 (Studi Kasus: Wilayah Pesisir Kota Tuban)","year":2024,"lang":"id","type":"article","venue":"EXTRAPOLASI","topic":"Geological and Geophysical Studies","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (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":[0.0008183331,0.0006493311,0.0006448909,0.001215731,0.001475514,0.002553069,0.0004697635,0.0007212208,0.008418441],"category_scores_gemma":[0.0008238496,0.0003914178,0.0008713287,0.001690727,0.0006351661,0.0009676937,0.0008057546,0.001068591,0.002811566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001037358,"about_ca_system_score_gemma":0.0008646263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01795421,"about_ca_topic_score_gemma":0.05392545,"domain_scores_codex":[0.9991969,0.00007157901,0.00005643411,0.0002763595,0.0002814954,0.0001172488],"domain_scores_gemma":[0.999071,0.0002078707,0.0001389805,0.00005988377,0.0004598202,0.00006233509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001290644,0.0003101926,0.2745309,0.002429401,0.0003282552,0.001019604,0.01036428,0.0008587259,0.6394733,0.0007948985,0.001885472,0.06671428],"study_design_scores_gemma":[0.00001229003,0.000753871,0.7783496,0.0002781394,0.0002961707,0.0006160318,0.01222996,0.0006345059,0.1666973,0.000533742,0.03951463,0.00008386912],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702203,0.002253927,0.003786382,0.0002153387,0.0000804241,0.0001971929,0.006076345,0.0001380224,0.01703208],"genre_scores_gemma":[0.9484124,0.002144764,0.009955977,0.0002341387,0.00001583875,0.0002830815,0.005272878,0.0002162195,0.03346477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01795421,"threshold_uncertainty_score":0.03569937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01829843298371263,"score_gpt":0.2251123834157332,"score_spread":0.2068139504320206,"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."}}