{"id":"W7095500661","doi":"","title":"Semidefinite Programming Relaxations in Timetabling","year":2011,"lang":"en","type":"article","venue":"","topic":"Nutrition, Health, and Society Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Semidefinite programming; Graph; Augmented Lagrangian method; Bounded function; Semidefinite embedding; Scheduling (production processes)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001841704,0.00004999074,0.00007756618,0.000006230421,0.0001845333,0.00001189635,0.00005647131,0.00004227218,0.0002388145],"category_scores_gemma":[0.00003018848,0.0000176525,0.00004020468,0.0003033103,0.0000247809,0.00007751396,0.00001713557,0.00006489782,0.00003353566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001106535,"about_ca_system_score_gemma":0.000002843527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001052804,"about_ca_topic_score_gemma":0.003074426,"domain_scores_codex":[0.9994899,0.00002506086,0.0001334633,0.0001164926,0.00006337889,0.0001717014],"domain_scores_gemma":[0.9998061,0.00007942136,0.0000288127,0.00001812309,0.00003258301,0.00003494071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002305668,0.0008064343,0.6854895,0.00003682633,0.00003004524,0.000007217103,0.007781252,8.425146e-7,0.006795441,0.02036788,0.003319899,0.2753416],"study_design_scores_gemma":[0.0001230997,0.00009758232,0.9553339,0.00002174333,0.000004866056,0.000002144981,0.003754943,0.00001604173,0.0001888727,0.003426257,0.03689437,0.0001361349],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707402,0.0003834908,0.00001208202,0.001019915,0.00006215347,0.0001837237,0.00000353922,0.0001056624,0.02748922],"genre_scores_gemma":[0.9941553,0.0004136179,0.00427359,0.0002650953,0.00006679617,0.00002684613,0.00001043454,3.264823e-7,0.0007879516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2752054,"threshold_uncertainty_score":0.2614851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07571898213349078,"score_gpt":0.2313499181449861,"score_spread":0.1556309360114954,"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."}}