{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002218983,0.00156989,0.0018363,0.001488595,0.00443498,0.01228704,0.001367283,0.003563035,0.7986135],"category_scores_gemma":[0.00431606,0.0007194322,0.001384762,0.001960104,0.0007070424,0.007815666,0.00482675,0.005902865,0.6355551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003262575,"about_ca_system_score_gemma":0.003328737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002468744,"about_ca_topic_score_gemma":0.006631635,"domain_scores_codex":[0.9987447,0.0001735236,0.00007526376,0.0003153219,0.0004391372,0.0002520723],"domain_scores_gemma":[0.9971268,0.0003059368,0.00009144102,0.0003389991,0.0008347788,0.001302061],"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":[0.00002200971,0.00001366894,0.00002418209,0.00002396032,0.000001163234,0.000007722887,0.00001521767,0.00001231512,0.00007125925,0.001550896,0.9911436,0.007114023],"study_design_scores_gemma":[0.00001193364,0.000008198316,0.000102177,0.00002992149,0.000001386562,0.00001319321,0.00003026721,0.00003135982,0.00004978459,0.001325596,0.998391,0.000005217089],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000508845,0.002815927,0.003684631,0.03332349,0.08057696,0.0004148615,0.01382903,0.005505538,0.8593406],"genre_scores_gemma":[0.004068188,0.001544677,0.0008879844,0.008010986,0.01720694,0.0003190021,0.006464917,0.003045058,0.9584523],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7986135,"threshold_uncertainty_score":0.2872533,"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."}}