{"id":"W3202629035","doi":"10.1017/s0022226721000293","title":"Licensing null arguments in recipes across languages","year":2021,"lang":"en","type":"article","venue":"Journal of Linguistics","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Western University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Null (SQL); Linguistics; Computer science; Null model; Context (archaeology); Variety (cybernetics); Recipe; Natural language processing; Mathematics; Artificial intelligence; History; Combinatorics; Philosophy; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0005431637,0.0001213485,0.0002946157,0.00009759641,0.0001264102,0.0002425197,0.000129701,0.00005633139,0.000233664],"category_scores_gemma":[0.01356272,0.0001150713,0.00009096799,0.0000551113,0.00006127694,0.00004168219,0.0000467912,0.0002859859,0.00002370501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009264183,"about_ca_system_score_gemma":0.0001165224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001700294,"about_ca_topic_score_gemma":0.00122584,"domain_scores_codex":[0.9985812,0.00006852661,0.0006810716,0.000116289,0.0003162961,0.0002365645],"domain_scores_gemma":[0.9974719,0.000269478,0.0004765603,0.0001481473,0.0015696,0.00006437359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000156763,0.0009558148,0.02051865,0.0002909029,0.0003736464,0.005423188,0.3328621,0.000405656,0.001066326,0.6284708,0.002157944,0.007318169],"study_design_scores_gemma":[0.004934145,0.0004537474,0.01257883,0.002885746,0.0004763238,0.0004072357,0.1583526,0.001732372,0.01071119,0.1758328,0.6303154,0.001319518],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8916276,0.00111327,0.0005597941,0.005106526,0.02203045,0.000131992,0.00007015443,0.00004904689,0.0793112],"genre_scores_gemma":[0.985224,0.00006310501,0.004035971,0.0002326141,0.009208675,2.910824e-7,0.000006427136,0.00002230301,0.001206603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6281575,"threshold_uncertainty_score":0.9947464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03500161447232062,"score_gpt":0.307804029249782,"score_spread":0.2728024147774613,"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."}}