{"id":"W2957152825","doi":"10.35791/agrsosek.15.1.2019.23585","title":"KONTRIBUSI USAHATANI KELAPA TERHADAP PENDAPATAN KELUARGA DI DESA KLABAT KECAMATAN DIMEMBE KABUPATEN MINAHASA UTARA","year":2019,"lang":"en","type":"article","venue":"AGRI-SOSIOEKONOMI","topic":"Agricultural and Environmental Management","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Agricultural science; Agriculture; Business; Family income; Descriptive statistics; Household income; Agricultural economics; Socioeconomics; Geography; Mathematics; Economics; Economic growth; Statistics; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028595,0.0002589762,0.0002042417,0.0005335001,0.001831193,0.001491833,0.0002333088,0.0002095789,0.01410085],"category_scores_gemma":[0.0005594586,0.000170432,0.0001062407,0.001008598,0.000437826,0.0007155177,0.0009410609,0.0003904449,0.001356337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008423416,"about_ca_system_score_gemma":0.001843412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006759723,"about_ca_topic_score_gemma":0.02255695,"domain_scores_codex":[0.9998351,0.00002510321,0.000009540268,0.00004105878,0.00003665818,0.00005240182],"domain_scores_gemma":[0.9995955,0.0001243549,0.00008557512,0.0000235409,0.0000790386,0.00009212788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004921063,0.0007510447,0.4753196,0.00158417,0.00006352529,0.01010772,0.04484443,0.0003286242,0.0305262,0.01020825,0.009850345,0.4159241],"study_design_scores_gemma":[0.00003283895,0.0003943383,0.7212555,0.0004605528,0.00007790313,0.006755592,0.07226025,0.0004499527,0.004896146,0.001752245,0.191606,0.00005861445],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9576315,0.001634374,0.0006602006,0.0005477135,0.0000718169,0.00008627148,0.000291932,0.00004913946,0.03902706],"genre_scores_gemma":[0.9747927,0.00138383,0.001500744,0.0001738099,0.00002070613,0.0001105428,0.0002871122,0.00001098215,0.02171965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01410085,"threshold_uncertainty_score":0.04717207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009858471012757835,"score_gpt":0.2238858705009592,"score_spread":0.2140273994882014,"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."}}