{"id":"W2969824606","doi":"10.32938/jpm.v1i1.185","title":"PENGGUNAAN REGRESI LINEAR MULTIPEL DAN METODE KUADRAT TERKECIL UNTUK MENGANALISISFAKTOR-FAKTOR YANG MEMPENGARUHI HASIL PRODUKSI JAGUNG DI KABUPATEN BELU","year":2019,"lang":"id","type":"article","venue":"RANGE Jurnal Pendidikan Matematika","topic":"Agricultural Development and Management","field":"Agricultural and Biological Sciences","cited_by":2,"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":[0.000879171,0.001396057,0.0008158548,0.0007456664,0.0006353201,0.001890662,0.0009572698,0.0008611821,0.02991015],"category_scores_gemma":[0.001212128,0.0006319173,0.001163197,0.0009720377,0.0004418919,0.001234539,0.001221856,0.001226248,0.01117276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007038973,"about_ca_system_score_gemma":0.0008399596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001759189,"about_ca_topic_score_gemma":0.002731963,"domain_scores_codex":[0.9992459,0.0001044818,0.00004112669,0.0001904463,0.0003164881,0.0001016215],"domain_scores_gemma":[0.9994037,0.0001978036,0.00007468401,0.0000936408,0.0001886554,0.00004142434],"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":[0.002331312,0.0004661434,0.005645063,0.002168269,0.00022876,0.0005087519,0.0006504495,0.03291418,0.5544142,0.009717483,0.01036284,0.3805926],"study_design_scores_gemma":[0.0001892391,0.002527497,0.01310384,0.0002158577,0.0005397968,0.0009654752,0.001112851,0.08254033,0.7423245,0.005714799,0.1504679,0.0002979288],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3784864,0.008298073,0.473346,0.001291167,0.0009827524,0.0005256721,0.003650386,0.009162851,0.1242566],"genre_scores_gemma":[0.7296118,0.003395664,0.1346979,0.0005550008,0.000145145,0.0005555229,0.002677659,0.001665809,0.1266955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02991015,"threshold_uncertainty_score":0.1000594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01978154415489602,"score_gpt":0.2264960331175723,"score_spread":0.2067144889626763,"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."}}