{"id":"W3201954736","doi":"10.33744/0365-8171-2021-110-165-179","title":"Proposals for improving of transport systemological terminology (part 5)","year":2021,"lang":"en","type":"article","venue":"Automobile Roads and Road Construction","topic":"linguistics and terminology studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"","keywords":"Terminology; Section (typography); Computer science; Data science; Linguistics; 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":[0.04798206,0.0008681824,0.0009533601,0.006836395,0.004859478,0.01096008,0.003581316,0.004796838,0.009974761],"category_scores_gemma":[0.04010589,0.0005379195,0.001802466,0.007668192,0.01764653,0.02260995,0.009787849,0.008099846,0.002497173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009900825,"about_ca_system_score_gemma":0.01632266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004652667,"about_ca_topic_score_gemma":0.002381387,"domain_scores_codex":[0.9705901,0.01902914,0.002957962,0.001581458,0.004504326,0.001337018],"domain_scores_gemma":[0.9700148,0.009740907,0.002429228,0.005443245,0.01152031,0.0008515407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001148223,0.00001402984,0.0002212424,0.0002163696,0.00000571496,0.00002077398,0.00273993,0.0002349734,0.0006009547,0.9736578,0.006520768,0.01575599],"study_design_scores_gemma":[0.00002880846,0.00009933929,0.001831116,0.001372713,0.0000536045,0.0002350873,0.008152564,0.002700607,0.002338507,0.4434578,0.5396613,0.00006859495],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03951924,0.02187922,0.5261565,0.1833874,0.01271585,0.001286762,0.0007765957,0.001016674,0.2132618],"genre_scores_gemma":[0.3077107,0.01078331,0.6235991,0.01911365,0.006081201,0.002100696,0.001771434,0.001145841,0.02769411],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04798206,"threshold_uncertainty_score":0.2537564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02663348817019691,"score_gpt":0.2345812310267171,"score_spread":0.2079477428565202,"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."}}