{"id":"W2171498092","doi":"","title":"The Characteristics of Phrasal Verbs in Marine Engineering English","year":2010,"lang":"en","type":"article","venue":"Studies in literature and language","topic":"Syntax, Semantics, Linguistic Variation","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Computer science; Feature (linguistics); Key (lock); Natural language processing; Artificial intelligence; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002149122,0.00008570221,0.0001543672,0.00006192669,0.0000566564,0.00006809532,0.00006482244,0.00003494632,0.00002231603],"category_scores_gemma":[0.001130763,0.00005884594,0.00001700621,0.00003962552,0.0001026846,0.00004991395,0.00006559864,0.0002397446,4.812065e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007466363,"about_ca_system_score_gemma":0.000004566427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008453799,"about_ca_topic_score_gemma":0.002299561,"domain_scores_codex":[0.9995169,0.00001327487,0.0001933535,0.00009258399,0.00006608905,0.0001177955],"domain_scores_gemma":[0.9995018,0.0002263599,0.00005078096,0.0001147608,0.00009513504,0.0000112027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001751287,0.00002238062,0.004911491,0.0001374301,0.00003185856,0.00003035045,0.7218456,2.661383e-7,0.0002769284,0.2702393,0.00004082745,0.002446108],"study_design_scores_gemma":[0.005126734,0.0004311061,0.3326509,0.002848439,0.0002091864,0.00002910306,0.4132261,0.001056369,0.00152519,0.05120264,0.1897698,0.001924462],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992521,0.001319564,5.372991e-7,0.0003373405,0.002590592,0.00008228898,0.00002519754,0.00001595446,0.003107461],"genre_scores_gemma":[0.9979505,0.0001673582,0.000116562,0.00003140176,0.001417687,0.000007433263,0.00001391796,0.000007834358,0.0002872821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3277394,"threshold_uncertainty_score":0.2399668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00800140147627697,"score_gpt":0.2345706049911271,"score_spread":0.2265692035148501,"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."}}