{"id":"W4255156961","doi":"10.3765/salt.v0i0.2947","title":"Remarks on \"only\"","year":2015,"lang":"en","type":"article","venue":"Proceedings from Semantics and Linguistic Theory","topic":"Multidisciplinary Warburg-centric Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Natural language processing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007114059,0.001132983,0.001120864,0.001416169,0.004479722,0.004409757,0.005007133,0.01299107,0.02504715],"category_scores_gemma":[0.03442968,0.0005898983,0.002019732,0.001178117,0.007507784,0.008449493,0.004372615,0.01745723,0.01784897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002589787,"about_ca_system_score_gemma":0.002605507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009319028,"about_ca_topic_score_gemma":0.00574599,"domain_scores_codex":[0.9930698,0.001494325,0.0005981536,0.001565601,0.002635469,0.0006365405],"domain_scores_gemma":[0.9857654,0.005068203,0.0006261377,0.001494027,0.0062946,0.0007517971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001127248,0.00002501154,0.0002133681,0.0002362971,0.00005212496,0.0001323889,0.0003075908,0.0001110402,0.0002228914,0.116884,0.8755419,0.006160699],"study_design_scores_gemma":[0.00006250762,0.00003229089,0.001337353,0.0004074961,0.00005988971,0.0001212973,0.0004667435,0.000336785,0.0004865785,0.1033639,0.8932577,0.00006740257],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.000998221,0.004152303,0.003351023,0.7567126,0.1600741,0.0000707951,0.0007186351,0.0004372892,0.07348509],"genre_scores_gemma":[0.03211078,0.002338782,0.00309396,0.840607,0.06193044,0.0003242807,0.000295579,0.0002333806,0.05906584],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02504715,"threshold_uncertainty_score":0.08379108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03316045043531882,"score_gpt":0.3132792962530597,"score_spread":0.2801188458177409,"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."}}