{"id":"W2619644040","doi":"10.30908/bilp.v3i2.179","title":"PENGEMBANGAN EKSPOR PRODUK KOMPONEN OTOMOTIF BERBAHAN BAKU KARET","year":2009,"lang":"id","type":"article","venue":"Buletin Ilmiah Litbang Perdagangan","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automotive industry; Natural rubber; Business; Commerce; Government (linguistics); Per capita; Product (mathematics); Raw material; Agricultural economics; International trade; Engineering; Economics; Chemistry; Mathematics; Population","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.001212515,0.001422714,0.001316535,0.0006277678,0.001028038,0.001771969,0.001785828,0.0006134032,0.00280492],"category_scores_gemma":[0.0003715315,0.001488176,0.000717297,0.001540009,0.0003082159,0.001434504,0.0004947712,0.001122209,0.01135933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002346716,"about_ca_system_score_gemma":0.0001819846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009222281,"about_ca_topic_score_gemma":0.0001499818,"domain_scores_codex":[0.9931289,0.000185897,0.001295598,0.002004083,0.00139332,0.001992231],"domain_scores_gemma":[0.9965543,0.0001315178,0.0007905008,0.001589255,0.0007090635,0.0002253757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003786588,0.01288098,0.07290079,0.008799823,0.00188646,0.009172617,0.005179517,0.00009604268,0.07361562,0.2595252,0.4798864,0.07227004],"study_design_scores_gemma":[0.002004082,0.0002552174,0.2176513,0.001018226,0.0004618655,0.00006806899,0.0009839691,0.0001027501,0.00309776,0.0007942392,0.7716271,0.001935428],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7492497,0.003486049,0.00004759573,0.04518067,0.003414262,0.002610117,0.0001661891,0.001312476,0.1945329],"genre_scores_gemma":[0.9515492,0.0001032934,0.0002489252,0.01018875,0.005957341,0.00006228889,0.0006073791,0.0002017924,0.03108103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2917407,"threshold_uncertainty_score":0.9998523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501336557465286,"score_gpt":0.2184303181391884,"score_spread":0.2034169525645355,"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."}}