{"id":"W6980795003","doi":"","title":"Corpus Construction for Terminology","year":2005,"lang":"en","type":"article","venue":"NPARC","topic":"Historical and Environmental Studies","field":"Social Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Terminology; Task (project management); Corpus linguistics; Semantics (computer science); Computational linguistics; Semantic Web","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":[0.00004341512,0.00002355154,0.00004319352,0.000007082481,0.0002923992,0.000003432795,0.00003658272,0.00002813789,0.0003785788],"category_scores_gemma":[0.00002414245,0.00002152815,0.00001976343,0.00002176326,0.0002246575,0.00003236826,0.000008698837,0.00001888771,0.00009457374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001015906,"about_ca_system_score_gemma":0.000006173225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005878815,"about_ca_topic_score_gemma":0.0002927062,"domain_scores_codex":[0.9997265,0.00001083911,0.00004306365,0.00006073386,0.00005210675,0.000106746],"domain_scores_gemma":[0.999903,0.0000273059,0.00001400907,0.00002414286,0.000004446231,0.00002705014],"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":[0.00001061776,0.00003364988,0.005006714,0.000002022751,0.000007047067,4.212188e-7,0.00302459,0.000001529752,0.002534055,0.07325785,0.02167108,0.8944504],"study_design_scores_gemma":[0.00007964659,0.00001648562,0.0007909458,5.046836e-7,0.000002852177,4.745402e-7,0.0003114057,0.000005212656,0.0001522211,0.007596411,0.9910124,0.00003143101],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2468763,0.0001472364,0.0008479903,0.01415923,0.0007771087,0.0002106166,0.000006443458,0.00007725946,0.7368978],"genre_scores_gemma":[0.9842778,0.0001121863,0.006660259,0.0002072841,0.000434851,0.00002241434,8.053368e-7,0.000002261326,0.008282122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9693413,"threshold_uncertainty_score":0.4145173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02400086460632959,"score_gpt":0.2655742728543821,"score_spread":0.2415734082480525,"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."}}