{"id":"W6987140561","doi":"","title":"Situation normal all FAHQT up: language, materiality and machine translation","year":2011,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Media, Communication, and Education","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McGill University","keywords":"Materiality (auditing); Translation (biology); Machine translation; Work (physics)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003005504,0.0005345803,0.000483377,0.001160734,0.002797115,0.008123695,0.0007787466,0.001885082,0.0364758],"category_scores_gemma":[0.0183328,0.0006053327,0.0006452842,0.001131307,0.003679058,0.01614756,0.003438617,0.003653959,0.009161875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001822279,"about_ca_system_score_gemma":0.00226817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004250776,"about_ca_topic_score_gemma":0.00252801,"domain_scores_codex":[0.9962954,0.002316617,0.0001205301,0.0004880773,0.0004345231,0.0003448143],"domain_scores_gemma":[0.9936681,0.003814961,0.0002005104,0.001152101,0.0008469173,0.0003172937],"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":[0.0006557524,0.0002253302,0.002913443,0.0002783992,0.00003979649,0.001523775,0.01650572,0.002168875,0.00475741,0.5476462,0.1204106,0.3028746],"study_design_scores_gemma":[0.00005523038,0.0001268287,0.003172844,0.0002665826,0.00004846212,0.001507366,0.01358132,0.0144063,0.006256345,0.7536906,0.2067437,0.0001444303],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1169541,0.003565309,0.1674687,0.06876761,0.003123281,0.0002326726,0.001821766,0.005414359,0.6326522],"genre_scores_gemma":[0.8896589,0.001237286,0.04165478,0.002123839,0.0006220547,0.0001080395,0.001396317,0.001786676,0.06141227],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.0364758,"threshold_uncertainty_score":0.1220238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05595558144620907,"score_gpt":0.3167081149475708,"score_spread":0.2607525335013618,"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."}}