{"id":"W4406704716","doi":"10.1007/s11049-024-09643-3","title":"Effects of uniqueness on extraction from definite NP objects","year":2025,"lang":"en","type":"article","venue":"Natural Language & Linguistic Theory","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"University of Delaware","keywords":"Uniqueness; Positive-definite matrix; Extraction (chemistry); Mathematics; Mathematical analysis; Chemistry; Physics; Chromatography","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":[0.0004502906,0.0002717391,0.0003335786,0.0003371167,0.0001093919,0.00009321891,0.001046767,0.0001980605,0.00001023103],"category_scores_gemma":[0.004724721,0.0002243824,0.0001183321,0.0005991234,0.0000885512,0.0001452679,0.0002337968,0.0006167974,0.00001206803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001048099,"about_ca_system_score_gemma":0.0001085209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002255418,"about_ca_topic_score_gemma":0.00001585878,"domain_scores_codex":[0.9982544,0.0003002949,0.0003195553,0.0005127797,0.0003166058,0.0002963868],"domain_scores_gemma":[0.9960572,0.002784629,0.0002156457,0.0006724139,0.0002145755,0.00005555101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001684244,0.0001219728,0.00002448608,0.000254318,0.00006305413,0.0003115931,0.002572166,0.000004081565,0.09472699,0.7683258,0.0001183933,0.1333087],"study_design_scores_gemma":[0.0004567147,0.00007909617,0.0002927727,0.0007204711,0.00005894985,0.000005913204,0.00006852209,0.0006821899,0.6835776,0.3134819,0.000266425,0.0003094414],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2187334,0.1389236,0.6071574,0.0003392224,0.008879719,0.001388831,0.00004408532,0.004025681,0.02050808],"genre_scores_gemma":[0.9162522,0.00001387144,0.0820519,0.0009096983,0.000165261,0.00001930258,0.00001613402,0.00001683743,0.0005548075],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6975188,"threshold_uncertainty_score":0.9150047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003218701715533618,"score_gpt":0.2718462062621694,"score_spread":0.2686275045466358,"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."}}