{"id":"W7001152790","doi":"","title":"Integrated Scheduling Problems in Healthcare and
\\nLogistics","year":2020,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Forensic Fingerprint Detection Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dynamic priority scheduling; Scheduling (production processes); Fair-share scheduling; Job shop scheduling; Nurse scheduling problem; Two-level scheduling; Rate-monotonic scheduling; Integer programming; Round-robin scheduling","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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00201152,0.000276748,0.0004933902,0.001445243,0.001237059,0.000239191,0.000633915,0.0006932157,0.00002992524],"category_scores_gemma":[0.001480593,0.0003409576,0.0001180603,0.002930002,0.0007699628,0.0002425349,0.0001381463,0.002852572,0.00002094128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001690669,"about_ca_system_score_gemma":0.003147743,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3004992,"about_ca_topic_score_gemma":0.5421163,"domain_scores_codex":[0.9942013,0.002713355,0.0003660657,0.0008749487,0.0009627331,0.0008815892],"domain_scores_gemma":[0.9979126,0.000559683,0.0002130815,0.0003214327,0.0004884988,0.0005047323],"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":[0.003352396,0.000473409,0.4661191,0.00438606,0.0006393663,0.007367865,0.09587414,0.0004392327,0.01250641,0.3518111,0.001525021,0.05550598],"study_design_scores_gemma":[0.003221107,0.002191922,0.1984984,0.003201527,0.0002020647,0.00003507052,0.2424287,0.003272751,0.01199422,0.02947837,0.502022,0.00345382],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8065055,0.0005257325,0.0002928519,0.004303073,0.002282441,0.001417793,0.00001283005,0.0003332548,0.1843265],"genre_scores_gemma":[0.9778855,0.0009116469,0.0005990822,0.0000176272,0.0003740407,0.000006862608,0.00005727143,0.00004864166,0.02009927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.500497,"threshold_uncertainty_score":0.9999042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06457185918198288,"score_gpt":0.3530846379887124,"score_spread":0.2885127788067295,"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."}}