{"id":"W3199063268","doi":"10.46806/ja.v9i2.762","title":"PENGARUH LEVEL DIVERSIFIKASI, JUMLAH SEGMEN, DAN JENIS SEKTOR INDUSTRI TERHADAP KINERJA PERUSAHAAN PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BURSA EFEK INDONESIA TAHUN 2016 – 2018","year":2020,"lang":"en","type":"article","venue":"Jurnal Akuntansi","topic":"Financial Analysis and Corporate Governance","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diversification (marketing strategy); Business; Business administration; Stock exchange; Competitor analysis; Variables; Secondary sector of the economy; Economics; Economy; Marketing; Finance; Mathematics; Statistics","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"],"consensus_categories":[],"category_scores_codex":[0.0003576994,0.000813368,0.0009220357,0.0002667229,0.000790276,0.0008197629,0.00111619,0.00029438,0.0005017277],"category_scores_gemma":[0.00009955595,0.0007131977,0.0004901511,0.001304796,0.0001812717,0.002318572,0.0007057909,0.0009544952,0.0007390263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002094031,"about_ca_system_score_gemma":0.0001641964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002384029,"about_ca_topic_score_gemma":0.0005030066,"domain_scores_codex":[0.9957502,0.00005586117,0.0009489722,0.001093144,0.00117269,0.0009791497],"domain_scores_gemma":[0.9978432,0.00005777336,0.001002202,0.000549651,0.0003632408,0.0001839365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001089956,0.0008075685,0.5797526,0.0006476219,0.0008027285,0.001801288,0.001161704,0.0004427036,0.01964358,0.003991968,0.3282437,0.06161457],"study_design_scores_gemma":[0.002867096,0.0001921564,0.4449177,0.0003383768,0.0006710747,0.00003533297,0.001855908,0.002611219,0.001470539,0.0002873047,0.5427371,0.002016227],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9825767,0.0004418936,0.0008086204,0.00904412,0.0008609194,0.0004933077,0.000104752,0.0002417442,0.005427985],"genre_scores_gemma":[0.9834889,0.0001199895,0.0002301895,0.008523078,0.004628484,0.00003125525,0.0001360102,0.0001137226,0.002728412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2144933,"threshold_uncertainty_score":0.9995319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03959166260522107,"score_gpt":0.1984531528482075,"score_spread":0.1588614902429865,"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."}}