{"id":"W2883003498","doi":"10.35791/agrsosek.14.1.2018.19557","title":"POTENSI PENGEMBANGAN TERNAK SAPI POTONG DENGAN POLA INTEGRASI KELAPA-SAPI DI KECAMATAN TABARU KABUPATEN HALMAHERA BARAT","year":2018,"lang":"en","type":"article","venue":"AGRI-SOSIOEKONOMI","topic":"Livestock Farming and Management","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Livestock; Agricultural science; Forage; Population; Beef cattle; Revenue; Productivity; Geography; Business; Animal science; Biology; Forestry; Ecology; Economic growth; Economics; Finance","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":[0.0001681667,0.0002496004,0.0001171237,0.0005039099,0.0006080525,0.0007263058,0.0002543324,0.0001820872,0.01030302],"category_scores_gemma":[0.0001762394,0.0001232582,0.0001319505,0.0006930101,0.0002180091,0.0004701454,0.0004777819,0.0002760173,0.0008426617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006444535,"about_ca_system_score_gemma":0.0009017981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006299999,"about_ca_topic_score_gemma":0.02890975,"domain_scores_codex":[0.9999067,0.00001139337,0.000004538458,0.0000217112,0.00002303508,0.00003268812],"domain_scores_gemma":[0.999873,0.00002335341,0.00003173396,0.000007515169,0.00003455732,0.00002983752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005876906,0.0005525055,0.5124348,0.0007720045,0.0001088545,0.004602152,0.01050575,0.00116729,0.03451589,0.005770603,0.005134662,0.4238478],"study_design_scores_gemma":[0.00003232614,0.0004000147,0.8967206,0.0001792293,0.0001119767,0.003224103,0.01886394,0.001518736,0.005231016,0.001366757,0.07231312,0.00003807988],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9772502,0.0008059031,0.0009286057,0.0002695989,0.00002145693,0.0000437749,0.0003159557,0.00003968144,0.02032497],"genre_scores_gemma":[0.984497,0.0005487553,0.001653899,0.0000786966,0.000009245789,0.00003654221,0.0003550134,0.00001073756,0.01281024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01030302,"threshold_uncertainty_score":0.03446704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01502937803275223,"score_gpt":0.2083282144331512,"score_spread":0.193298836400399,"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."}}