{"id":"W4387216787","doi":"10.59697/jik.v4i2.331","title":"SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN CALON TENAGA PENDIDIK DENGAN MENGGUNAKAN METODEMULTI-OBJECTIVE OPTIMAZTION ON THE BASIS OF RATIO ANALYSIS(MOORA) (StudiKasus: Yayasan Perguruan Swakarya)","year":2020,"lang":"id","type":"article","venue":"Jurnal Informatika Kaputama (JIK)","topic":"Decision Support System Applications","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Humanities; Psychology; Mathematics; Art","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.002826569,0.001337807,0.002214736,0.001717938,0.001916104,0.002055473,0.002122052,0.0004796658,0.00471406],"category_scores_gemma":[0.0009031571,0.001026257,0.001635477,0.00629334,0.0003499382,0.004903323,0.001009639,0.001359914,0.004880941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004979108,"about_ca_system_score_gemma":0.0003513534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000363131,"about_ca_topic_score_gemma":0.0001929107,"domain_scores_codex":[0.9903247,0.0003664954,0.004062812,0.001147586,0.002918822,0.001179574],"domain_scores_gemma":[0.9908135,0.0008353906,0.004553508,0.001676743,0.001799691,0.0003211716],"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":[0.006758886,0.008070123,0.1002769,0.01181732,0.05663988,0.0004992004,0.08568843,0.03036219,0.02732305,0.09521589,0.5329124,0.04443572],"study_design_scores_gemma":[0.01075617,0.001500701,0.259118,0.002004685,0.02223661,0.0001238791,0.1401826,0.1855075,0.01535619,0.0003166601,0.3558757,0.007021238],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3807329,0.001290688,0.01497596,0.02434645,0.002095419,0.008630331,0.0005628542,0.0008554664,0.5665099],"genre_scores_gemma":[0.9913438,0.0001238718,0.0005418501,0.003030272,0.001123445,0.0002669636,0.0005728751,0.0001444189,0.00285252],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6106108,"threshold_uncertainty_score":0.9999373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04410420010325458,"score_gpt":0.2597768754082206,"score_spread":0.2156726753049661,"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."}}