{"id":"W4320737743","doi":"10.1145/3584667.3584669","title":"SIGCSE Technical Symposium 2023: Information for Attendees","year":2023,"lang":"en","type":"article","venue":"ACM SIGCSE Bulletin","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Craft; Convention; Computer science; Library science; Work (physics); Engineering ethics; Political science; Engineering; Law; History","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006971397,0.0001688827,0.0002399417,0.0005782783,0.000364931,0.0008509945,0.002312128,0.00008948933,0.0008399844],"category_scores_gemma":[0.01577946,0.0001320485,0.000168169,0.001524514,0.00009858711,0.000293701,0.001622639,0.0001228196,0.02259283],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003878028,"about_ca_system_score_gemma":0.00003751149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002621408,"about_ca_topic_score_gemma":0.000008465746,"domain_scores_codex":[0.9966357,0.00009433879,0.0008161686,0.0006274496,0.001353904,0.0004724396],"domain_scores_gemma":[0.994131,0.003133591,0.0002457778,0.00204838,0.0003043087,0.0001369607],"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":[0.00002721398,0.00002273849,0.0001593292,0.000008455308,0.000006649784,0.000003006587,0.0001138996,0.0006512431,0.0001542238,0.0008009045,0.9576709,0.04038148],"study_design_scores_gemma":[0.0004006209,0.00006668036,0.002283138,0.00001460547,0.00001077546,0.000003683524,0.0005484987,0.00294451,0.000213765,0.006783749,0.9865432,0.0001867693],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2157939,0.0001315198,0.1438563,0.493278,0.01835021,0.00639479,0.00119658,0.004955258,0.1160435],"genre_scores_gemma":[0.8794481,0.00004679127,0.02252489,0.005473614,0.0008025009,0.0004549572,0.0008028471,0.00004955387,0.09039672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6636543,"threshold_uncertainty_score":0.992511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1073250021293284,"score_gpt":0.3760461996327965,"score_spread":0.2687211975034681,"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."}}