{"id":"W4396230899","doi":"10.31328/js.v7i1.5583","title":"Optimalisasi Laboratorium Terpadu Guna Mendukung Kuliah Penelitian dan Kuliah Pengabdian Kepada Masyarakat Dengan Introduksi PIOS-RT","year":2024,"lang":"id","type":"article","venue":"JURNAL APLIKASI DAN INOVASI IPTEKS SOLIDITAS (J-SOLID)","topic":"Management and Optimization Techniques","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Computer science","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":[0.004544711,0.001142153,0.001229205,0.001544026,0.001266411,0.004952942,0.001301398,0.00143074,0.01720156],"category_scores_gemma":[0.003090916,0.000849363,0.00127514,0.001244518,0.0009263318,0.002171654,0.001893828,0.002197965,0.007317754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002355939,"about_ca_system_score_gemma":0.006517027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007336511,"about_ca_topic_score_gemma":0.01315781,"domain_scores_codex":[0.9950777,0.0009705893,0.0003467484,0.0009226386,0.002194034,0.0004884131],"domain_scores_gemma":[0.9974323,0.0004501332,0.0003998485,0.0003390918,0.001150176,0.0002284519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002187763,0.001552044,0.03817933,0.002540721,0.0001872557,0.0007761563,0.001741499,0.001715739,0.6848534,0.005398702,0.01422137,0.246646],"study_design_scores_gemma":[0.0001595245,0.003163186,0.04536326,0.0005676674,0.0003789034,0.001127318,0.002511604,0.003706595,0.7022813,0.002835844,0.237712,0.0001929133],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6325083,0.01731766,0.1654571,0.009239211,0.002046209,0.00433481,0.01113869,0.008391856,0.1495662],"genre_scores_gemma":[0.6989423,0.008539128,0.1728996,0.002198793,0.0002823183,0.002214574,0.007958892,0.001358395,0.105606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01720156,"threshold_uncertainty_score":0.05754501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0151795138863523,"score_gpt":0.2588733527582872,"score_spread":0.2436938388719349,"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."}}