{"id":"W6931224636","doi":"10.5281/zenodo.4242888","title":"TATA KELOLA DAN PUBLISHING MANAGEMENT OPEN JOURNAL SYSTEM","year":2020,"lang":"id","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"License; Publication; Publishing","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009532043,0.0007873261,0.001098394,0.007960895,0.006126371,0.02942031,0.002497798,0.003289854,0.1932506],"category_scores_gemma":[0.0331503,0.0009269667,0.001035076,0.01002526,0.00220832,0.01903062,0.00761581,0.003336603,0.2138332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002471158,"about_ca_system_score_gemma":0.01014028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001869072,"about_ca_topic_score_gemma":0.001566321,"domain_scores_codex":[0.9901512,0.002057857,0.001765056,0.001269036,0.004056613,0.0007002178],"domain_scores_gemma":[0.9578087,0.008241344,0.004439169,0.01151034,0.01044695,0.007553532],"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":[0.000316518,0.0002027572,0.002213061,0.001479267,0.00008762614,0.0005244106,0.002167698,0.0002533371,0.002684518,0.06600836,0.6518931,0.2721694],"study_design_scores_gemma":[0.00003510089,0.00003504226,0.0008875527,0.0001598102,0.00002731904,0.0002698582,0.0003424006,0.000375841,0.0007426101,0.007836483,0.9892372,0.0000506639],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01022134,0.005687182,0.06600464,0.02799209,0.01016284,0.002096345,0.01748535,0.08277757,0.7775726],"genre_scores_gemma":[0.06461177,0.008360195,0.04063267,0.005686515,0.00679563,0.001639623,0.01936533,0.01195974,0.8409485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9705797,"threshold_uncertainty_score":0.6464876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07165003432926895,"score_gpt":0.259858932817174,"score_spread":0.1882088984879051,"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."}}