{"id":"W7098089710","doi":"","title":""In Search of Terms: An Empirical Approach to Lexicography" In Search of Terms: An Empirical Approach","year":2015,"lang":"en","type":"article","venue":"","topic":"linguistics and terminology studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Promotion (chess); Empirical research; Work (physics); Order (exchange); Empirical evidence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001419529,0.0004249552,0.0009772471,0.001083151,0.0001694217,0.0001269067,0.0007602898,0.0002412756,0.0001236442],"category_scores_gemma":[0.0001999957,0.0003316471,0.00017549,0.0003928525,0.001298301,0.0002140139,0.0004596605,0.0006069116,0.00002711843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008012882,"about_ca_system_score_gemma":0.0001637977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002362108,"about_ca_topic_score_gemma":0.006082469,"domain_scores_codex":[0.9960432,0.0004347246,0.000984243,0.0008761336,0.0007557323,0.000905958],"domain_scores_gemma":[0.9980264,0.0001715544,0.000110563,0.000857041,0.0004425941,0.0003918685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004031335,0.006627807,0.6626815,0.0003411252,0.0001834672,0.00002046461,0.2794721,0.0001862873,0.00007116554,0.0420069,0.005801341,0.00220471],"study_design_scores_gemma":[0.01415572,0.008643216,0.4118912,0.0004270584,0.0003609846,0.0001055146,0.2749173,0.0117544,0.0009490196,0.02667394,0.2446476,0.005474027],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8329691,0.00009842557,0.0003345416,0.0002675756,0.0001711795,0.0005829859,0.00007916731,0.00006841526,0.1654287],"genre_scores_gemma":[0.9882742,0.00001477854,0.007261112,0.000342445,0.0004818246,0.00007829079,0.0001331215,0.00005219441,0.003362052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2507902,"threshold_uncertainty_score":0.9999136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3480086064851375,"score_gpt":0.3980991775126925,"score_spread":0.05009057102755493,"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."}}