{"id":"W6963348136","doi":"10.20381/ruor-25399","title":"Qamani’tuac","year":2018,"lang":"en","type":"article","venue":"University of Ottawa - Library","topic":"Travel Writing and Literature","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Officer; Coast guard; Government (linguistics); Guard (computer science); Order (exchange)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007437358,0.0005764953,0.0004826449,0.000968546,0.005852363,0.002735174,0.0006851818,0.0009172239,0.2772143],"category_scores_gemma":[0.00205813,0.0002728631,0.0003565443,0.001318441,0.0009201093,0.001397951,0.001127497,0.00133025,0.06825796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003631245,"about_ca_system_score_gemma":0.006604234,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04945746,"about_ca_topic_score_gemma":0.0861876,"domain_scores_codex":[0.9996062,0.00004535868,0.00002744704,0.0000787051,0.0001421199,0.000100228],"domain_scores_gemma":[0.9989121,0.0001073767,0.00007557288,0.00005751979,0.0006551564,0.0001922283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003375324,0.0001271988,0.008259302,0.0009571259,0.00002935799,0.002750264,0.006606896,0.0002497082,0.003357166,0.05069695,0.55083,0.3757985],"study_design_scores_gemma":[0.000007347225,0.00003227391,0.00361887,0.0001434348,0.000008172336,0.00116985,0.002425586,0.0001289775,0.0004904025,0.0008447287,0.9911192,0.00001119003],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03313028,0.02034293,0.002612072,0.02512909,0.01447986,0.000225779,0.001559051,0.000690896,0.90183],"genre_scores_gemma":[0.07337079,0.005632018,0.001934032,0.002446498,0.0006463773,0.00005382839,0.0005762799,0.0001631622,0.915177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9505426,"threshold_uncertainty_score":0.9273741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009143866423864022,"score_gpt":0.1504011213442344,"score_spread":0.1412572549203704,"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."}}