{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007565374,0.003902832,0.002619619,0.005686845,0.003906857,0.01449662,0.002303825,0.00467846,0.5915472],"category_scores_gemma":[0.01371295,0.001629961,0.0018785,0.005895829,0.000643424,0.007664272,0.005253815,0.005469332,0.6636676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002302119,"about_ca_system_score_gemma":0.006835832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007086282,"about_ca_topic_score_gemma":0.01269996,"domain_scores_codex":[0.9964318,0.0005344693,0.0002566352,0.0003080639,0.001979364,0.0004894779],"domain_scores_gemma":[0.984943,0.001095546,0.0006062334,0.001010234,0.006900417,0.005444577],"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":[0.00002125239,0.00002650607,0.00008531445,0.00006648422,0.000002956132,0.00002463541,0.0000098441,0.00002226031,0.0001115324,0.0001323394,0.9820122,0.01748461],"study_design_scores_gemma":[0.00002616961,0.00003112776,0.0004649355,0.0001138676,0.000008017289,0.00003778443,0.00005970887,0.0001386933,0.0001394988,0.0002940024,0.9986671,0.00001903923],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003052786,0.01882727,0.01365411,0.05755402,0.1414348,0.003871664,0.06024283,0.0232391,0.6781234],"genre_scores_gemma":[0.003920884,0.01159153,0.004453366,0.007567315,0.02107835,0.002496071,0.0317755,0.005109131,0.9120077],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5915472,"threshold_uncertainty_score":0.5826083,"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."}}