{"id":"W4378603662","doi":"10.1007/978-3-031-33231-9_2","title":"A Parsing Tool for Short Linguistic Constructions","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Parsing; Linguistics; Computer science; Natural language processing; Artificial intelligence; Philosophy","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":[0.001064332,0.002156349,0.00158085,0.004027965,0.00155616,0.003584699,0.002239788,0.00153859,0.067725],"category_scores_gemma":[0.004530421,0.001931223,0.001788554,0.005261451,0.001073672,0.00655142,0.003057254,0.002667053,0.02938707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007348732,"about_ca_system_score_gemma":0.001324361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001426957,"about_ca_topic_score_gemma":0.001622191,"domain_scores_codex":[0.9990477,0.0002160061,0.0001404346,0.0002287837,0.0002958643,0.00007127842],"domain_scores_gemma":[0.9969297,0.001938231,0.0001171437,0.0004547338,0.000492129,0.00006798351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001959767,0.00009185129,0.0004512126,0.0008105512,0.00006413146,0.0005526989,0.0009430964,0.00225035,0.01228578,0.1370471,0.2246909,0.6206163],"study_design_scores_gemma":[0.0001029638,0.00006369858,0.0005764192,0.0004978104,0.000175815,0.001463146,0.0003970998,0.07257588,0.04083334,0.2716,0.6115363,0.0001776312],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00246146,0.0004275223,0.8857943,0.0003684243,0.0002722083,0.0001510396,0.005159922,0.08861632,0.01674888],"genre_scores_gemma":[0.04685364,0.0009564436,0.8576975,0.0005372108,0.0002827624,0.0006094796,0.02181621,0.03658649,0.03466037],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.067725,"threshold_uncertainty_score":0.2265627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04977500912787741,"score_gpt":0.3331279007641301,"score_spread":0.2833528916362527,"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."}}