{"id":"W2341697101","doi":"10.29244/jitl.16.1.24-30","title":"POTENSI LAHAN UNTUK KOLAM IKAN DI KABUPATEN CIANJUR BERDASARKAN ANALISIS KESESUAIAN LAHAN MULTI KRITERIA","year":2014,"lang":"id","type":"article","venue":"Jurnal Ilmu Tanah dan Lingkungan","topic":"Marine and Coastal Ecosystems","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Physics; Forestry; 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","insufficient_payload"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.001674497,0.001352724,0.001520046,0.0004413964,0.001223089,0.001022552,0.001888539,0.0006569116,0.0007628073],"category_scores_gemma":[0.000329188,0.001328529,0.0007878132,0.001348638,0.0005183302,0.0009843863,0.001298111,0.001385389,0.001493311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005716483,"about_ca_system_score_gemma":0.0001217167,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008764439,"about_ca_topic_score_gemma":0.01472207,"domain_scores_codex":[0.9915859,0.0009198462,0.001844749,0.001944294,0.001551399,0.002153877],"domain_scores_gemma":[0.9950516,0.0001721426,0.001111387,0.001822193,0.0001615069,0.001681136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006173405,0.002640831,0.6706678,0.0007220792,0.001180365,0.001027628,0.004723179,0.0006257303,0.1877929,0.001664789,0.01118123,0.1171562],"study_design_scores_gemma":[0.004112921,0.002148131,0.5790637,0.001068327,0.0008568168,0.0003880945,0.00302142,0.03545786,0.01669035,0.0002141649,0.3528074,0.00417076],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9698643,0.0003440348,0.0005139497,0.001419145,0.002283618,0.0008706311,0.0002563528,0.0002799184,0.02416804],"genre_scores_gemma":[0.9862856,0.0002217215,0.0006141808,0.001074544,0.001764596,0.00003234244,0.0001968168,0.0002422459,0.009568007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3416262,"threshold_uncertainty_score":0.9999224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01302640820528125,"score_gpt":0.2310762294717534,"score_spread":0.2180498212664722,"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."}}