{"id":"W2230023253","doi":"10.1093/jos/ffw006","title":"Training and Timing Local Scalar Enrichments under Global Pragmatic Pressures","year":2016,"lang":"en","type":"article","venue":"Journal of Semantics","topic":"Neurobiology of Language and Bilingualism","field":"Neuroscience","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Agence Nationale de la Recherche","keywords":"Meaning (existential); Sentence; Linguistics; Mechanism (biology); Comprehension; Reading comprehension; Interpretation (philosophy); Reading (process); Computer science; Reciprocal; Relation (database); Psychology; Artificial intelligence; Epistemology; Philosophy; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002691767,0.00009966429,0.0002012634,0.00004823452,0.00007163343,0.00003066687,0.0001658505,0.00005911846,0.00001809872],"category_scores_gemma":[0.0004231081,0.00005737926,0.00005046139,0.00007134851,0.0001976649,0.0001786958,0.00005760276,0.0001091707,0.000005276234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001915513,"about_ca_system_score_gemma":0.00004285339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.185245e-7,"about_ca_topic_score_gemma":0.000001252174,"domain_scores_codex":[0.9990368,0.0001083106,0.0003040915,0.0001339075,0.0002161919,0.0002007161],"domain_scores_gemma":[0.9992024,0.0003179625,0.0002591876,0.00008912975,0.00004258879,0.00008875441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008350729,0.0002124635,0.003071199,0.0000833848,0.00006760735,0.003117645,0.001961151,0.00009463848,0.9307852,0.002026822,0.0005839518,0.05791237],"study_design_scores_gemma":[0.01435072,0.00487091,0.0182903,0.003954718,0.001157223,0.09825863,0.006879066,0.002021671,0.7541844,0.07407089,0.01973969,0.002221803],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879736,0.0002125234,0.009572642,0.00157035,0.0003478415,0.00005234664,0.000004153769,0.00001246914,0.0002540714],"genre_scores_gemma":[0.9981784,0.0001155542,0.0005333674,0.000906994,0.0001356007,2.023046e-7,6.456563e-8,0.000006859797,0.0001229285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1766009,"threshold_uncertainty_score":0.2339858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05014074015318835,"score_gpt":0.3187917940705155,"score_spread":0.2686510539173271,"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."}}