{"id":"W4391556103","doi":"10.4230/lipics.fscd.2024.15","title":"Adjoint Natural Deduction","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Natural deduction; Natural (archaeology); Mathematics; Computer science; Mathematical economics; Programming language; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003519272,0.0004998003,0.0006355194,0.001417542,0.001278015,0.002687196,0.001657976,0.0008678102,0.007336132],"category_scores_gemma":[0.006404719,0.000480678,0.001395841,0.001121668,0.003561375,0.003862597,0.003156919,0.002833497,0.001698832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001342253,"about_ca_system_score_gemma":0.001507301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007887516,"about_ca_topic_score_gemma":0.001035241,"domain_scores_codex":[0.9976314,0.0006889784,0.0001522347,0.0005258624,0.0008122129,0.0001891612],"domain_scores_gemma":[0.9971244,0.001569365,0.0001203025,0.000566349,0.0005157031,0.0001038953],"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":[0.00002583207,0.00002836259,0.0001847173,0.000101246,0.00001567588,0.0001310235,0.000255991,0.0009780457,0.001367292,0.9578943,0.00395953,0.035058],"study_design_scores_gemma":[0.00002244764,0.00002135159,0.00009194839,0.00003465673,0.00001690731,0.0002014714,0.00004532461,0.01106188,0.003206339,0.9352509,0.05003009,0.00001658564],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00532442,0.0002816536,0.9628761,0.0009658239,0.0003560272,0.0001016828,0.0002684061,0.001645458,0.02818055],"genre_scores_gemma":[0.2409772,0.0005294668,0.7375325,0.001453217,0.0004230744,0.0002535056,0.0006970191,0.0006079477,0.01752604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007336132,"threshold_uncertainty_score":0.02454185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04104605341892123,"score_gpt":0.19785011631357,"score_spread":0.1568040628946488,"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."}}