{"id":"W7062355805","doi":"","title":"A Survey of Indigenous Language Tools: The Mergence of Two Lexicographical Approaches among Indigenous Languages of Canada","year":2019,"lang":"en","type":"article","venue":"Americanae (AECID Library)","topic":"Particle Detector Development and Performance","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Indigenous; Lexicographical order; Lexicography; Computational linguistics; Tracing; Lexical item","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":[0.003085474,0.0005451488,0.0006050325,0.01945601,0.006911427,0.006272313,0.002046121,0.000465106,0.00816552],"category_scores_gemma":[0.0110372,0.0003429585,0.0004085327,0.03616399,0.004867537,0.004010802,0.003410072,0.000853516,0.001411005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02702368,"about_ca_system_score_gemma":0.08782476,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9554793,"about_ca_topic_score_gemma":0.9739871,"domain_scores_codex":[0.9966276,0.000248622,0.0002596925,0.0003758325,0.001923869,0.0005643173],"domain_scores_gemma":[0.9872291,0.003016139,0.0006972947,0.0006199643,0.007209223,0.001228217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002727925,0.00007484757,0.07857277,0.003930736,0.0001120001,0.001012779,0.08035455,0.0006891321,0.006094772,0.05523824,0.04394904,0.7296984],"study_design_scores_gemma":[0.00001373372,0.00005126705,0.1352012,0.002537,0.0001441185,0.001488335,0.06634694,0.0009132047,0.003721151,0.004259391,0.7851408,0.0001829383],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4908554,0.07671051,0.03324809,0.01281309,0.000501245,0.0006295123,0.02358784,0.00327907,0.3583753],"genre_scores_gemma":[0.7926746,0.07477085,0.0644601,0.00221729,0.00009344317,0.0002227431,0.01717409,0.001793575,0.04659329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04452074,"threshold_uncertainty_score":0.1960714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01526261464855462,"score_gpt":0.2203743266577808,"score_spread":0.2051117120092262,"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."}}