{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002280702,0.000428795,0.0004334661,0.0002765312,0.001533408,0.0001690136,0.0006056675,0.0007722456,0.0009927404],"category_scores_gemma":[0.0005619503,0.0004832101,0.0001394772,0.000342979,0.0001227673,0.001224846,0.00004242605,0.0006730164,0.0001603831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003178437,"about_ca_system_score_gemma":0.0001166604,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01780206,"about_ca_topic_score_gemma":0.0663804,"domain_scores_codex":[0.9962979,0.001099914,0.0007255552,0.0006282222,0.0007182153,0.0005301723],"domain_scores_gemma":[0.9978817,0.0002096823,0.0005809096,0.0006411094,0.0003464602,0.0003401141],"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":[0.000415614,0.0003192777,0.0003031718,0.0004826817,0.0001742234,0.000004518734,0.02552671,0.000001760807,0.01559697,0.07951318,0.00002305008,0.8776388],"study_design_scores_gemma":[0.005898815,0.0005410864,0.0668594,0.001622714,0.002405166,0.00002761361,0.08621161,0.0001379354,0.08939859,0.1532528,0.5864981,0.007146211],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8754504,0.0009975927,0.000001052657,0.00006850259,0.002939173,0.0007494022,0.0003628002,0.0002259144,0.1192051],"genre_scores_gemma":[0.9812071,0.002112638,0.0007179277,0.0001269348,0.0002014246,0.0001252689,0.005760382,0.00007940271,0.00966891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8704926,"threshold_uncertainty_score":0.9999205,"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."}}