{"id":"W4239917916","doi":"10.1515/iupac.83.0451","title":"Scheduling Software","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Computer science; Field (mathematics); Data science; Multidisciplinary approach; Context (archaeology); Process (computing); Software; Management science; Engineering; Sociology; Biology; Linguistics; Programming language","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002776107,0.0004836677,0.0005203518,0.0002613419,0.00009605389,0.00009125537,0.0004129822,0.0005040056,0.002398157],"category_scores_gemma":[0.0005112084,0.0004118253,0.000155203,0.0002341129,0.00006283853,0.000101379,0.00007539103,0.0005794018,0.000013054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003390809,"about_ca_system_score_gemma":0.0002459521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008840099,"about_ca_topic_score_gemma":0.00004120807,"domain_scores_codex":[0.9979497,0.00002776905,0.0004538569,0.0003704491,0.0007368672,0.0004613732],"domain_scores_gemma":[0.9985937,0.00009044007,0.00008941301,0.0006917869,0.0003312621,0.0002033598],"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":[0.00001047206,0.00002760367,0.00000189717,0.0001588131,0.00009816195,0.00002616217,0.000006466341,0.02057112,0.00000126215,0.00000127147,0.9728107,0.006286063],"study_design_scores_gemma":[0.000554267,0.00003209734,0.000001618908,0.0004604114,0.00006954507,0.00001202644,0.00001281854,0.005145325,0.00002080717,0.00003511545,0.9930993,0.0005566889],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001415974,0.001641931,0.07048196,0.00007672613,0.002084682,0.0001375626,0.9247515,0.0007894391,0.00002210895],"genre_scores_gemma":[0.000001785982,0.001478863,0.02750858,0.0001060085,0.001375357,0.00001409655,0.9692664,0.000106769,0.0001421432],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04451496,"threshold_uncertainty_score":0.9998333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01081816398983383,"score_gpt":0.3328602081829691,"score_spread":0.3220420441931353,"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."}}