{"id":"W561883102","doi":"10.1017/jsl.2016.12","title":"COMPUTABLE FUNCTORS AND EFFECTIVE INTERPRETABILITY","year":2017,"lang":"en","type":"preprint","venue":"Journal of Symbolic Logic","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Division of Mathematical Sciences; National University of Singapore; City University of New York; National Science Foundation","keywords":"Interpretability; Functor; Equivalence (formal languages); Mathematics; Algebra over a field; Pure mathematics; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003070029,0.0006014982,0.001632897,0.0003700368,0.0002536604,0.0009922341,0.003736082,0.0004663843,0.00002142356],"category_scores_gemma":[0.0009321361,0.0004610946,0.0005624518,0.0001602176,0.0004212339,0.000642021,0.006394757,0.002015489,0.00001379766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004091461,"about_ca_system_score_gemma":0.0004636747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007957136,"about_ca_topic_score_gemma":0.000005778034,"domain_scores_codex":[0.9959869,0.0006266254,0.001145508,0.0009497667,0.0007525394,0.0005386187],"domain_scores_gemma":[0.9940028,0.000859496,0.002022896,0.001884362,0.0008346694,0.0003957972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003047309,0.002434182,0.08117048,0.002496421,0.001887008,0.00115052,0.01291643,0.01838539,0.0004387868,0.02067607,0.003025402,0.8551146],"study_design_scores_gemma":[0.001483037,0.001454983,0.2144195,0.0007915857,0.0002038055,0.001410533,0.00006861542,0.1003343,0.0002706873,0.6766788,0.001677083,0.001207057],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3817952,0.004142338,0.6004022,0.001939296,0.007959307,0.001049596,0.00001351275,0.0001596728,0.002538831],"genre_scores_gemma":[0.9642252,0.0001485993,0.03463069,0.0002021101,0.0007187623,0.00001419753,0.000001288431,0.0000211539,0.00003800057],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8539075,"threshold_uncertainty_score":0.9997841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01987077277641092,"score_gpt":0.284151043736508,"score_spread":0.264280270960097,"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."}}