{"id":"W3137835047","doi":"10.1145/3262168","title":"Session details: Semantics","year":2015,"lang":"en","type":"article","venue":"ACM SIGLOG News","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Column (typography); Session (web analytics); Semantics (computer science); Component (thermodynamics); Foundation (evidence); Connection (principal bundle); Subject (documents); Computer science; Quarter (Canadian coin); Mathematics education; Mathematics; Theoretical computer science; Algebra over a field; Pure mathematics; Programming language; World Wide Web; Political science; History; Geometry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000294098,0.0001444353,0.0001745743,0.0000586753,0.00009084067,0.0001481506,0.001552885,0.00009884435,0.00001610833],"category_scores_gemma":[0.00072649,0.0001097123,0.00006162659,0.0003009134,0.00003747797,0.0004102502,0.0008515476,0.0001318157,0.0009643966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004407678,"about_ca_system_score_gemma":0.0001384934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004978666,"about_ca_topic_score_gemma":0.00005996107,"domain_scores_codex":[0.9988193,0.00008428409,0.0001766639,0.0003464186,0.0002477689,0.0003255961],"domain_scores_gemma":[0.9983247,0.000123075,0.0000806946,0.001111288,0.0001245127,0.0002357388],"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":[0.00002512552,0.0004430294,0.08464901,0.00004744807,0.00005577632,0.0003796289,0.009862758,0.00009176569,0.002630858,0.169882,0.4551613,0.2767713],"study_design_scores_gemma":[0.002859524,0.0007433529,0.01027584,0.0001037388,0.00004684714,0.0002855521,0.0007340852,0.02942294,0.01054339,0.210849,0.732722,0.001413796],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1633245,0.002703107,0.6334416,0.008275857,0.005583134,0.0005086427,0.000002159147,0.001415945,0.1847451],"genre_scores_gemma":[0.9516199,0.00004441632,0.04400765,0.0008869995,0.0003348278,0.000008242878,0.000002934142,0.00001279178,0.003082203],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7882954,"threshold_uncertainty_score":0.9998135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05597036807902019,"score_gpt":0.2860830191579579,"score_spread":0.2301126510789377,"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."}}