{"id":"W4387030715","doi":"10.48550/arxiv.2309.12466","title":"Mechanizing Session-Types using a Structural View: Enforcing Linearity without Linearity","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Session (web analytics); Linearity; Computer science; Channel (broadcasting); Syntax; Linear logic; Encoding (memory); Programming language; Theoretical computer science; Abstract syntax; Artificial intelligence; Computer network; Electronic engineering; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006316875,0.0004874901,0.0005180333,0.000859468,0.001479997,0.003597727,0.002848708,0.00147446,0.007499485],"category_scores_gemma":[0.01471857,0.001119321,0.001704588,0.0007964567,0.006452781,0.01027582,0.007865678,0.005454826,0.001699367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002046924,"about_ca_system_score_gemma":0.00518354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003079466,"about_ca_topic_score_gemma":0.003478214,"domain_scores_codex":[0.9947573,0.001872662,0.0003920161,0.0007357395,0.001575858,0.0006664378],"domain_scores_gemma":[0.9889157,0.005341529,0.0005079715,0.003465773,0.001421354,0.0003476598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006536696,0.00005381505,0.0006675574,0.0001275188,0.00002571993,0.0001714913,0.001034186,0.006203882,0.007611082,0.9658217,0.001667893,0.01654984],"study_design_scores_gemma":[0.0001271699,0.0001339848,0.0004782692,0.0001377906,0.0001442071,0.0003694426,0.0006031186,0.0757881,0.06108234,0.8253493,0.03565635,0.0001299718],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0186875,0.0000538179,0.9699991,0.0008471134,0.00009751708,0.00009095549,0.0001168403,0.002475391,0.007631805],"genre_scores_gemma":[0.5482572,0.0003128265,0.4369681,0.001101828,0.0001603914,0.000355624,0.0002465044,0.001217436,0.01138018],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007499485,"threshold_uncertainty_score":0.03340721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1395796455650823,"score_gpt":0.2425565025239181,"score_spread":0.1029768569588358,"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."}}