{"id":"W2415309954","doi":"","title":"In Search of an Effective Method of Measuring Aboriginal Children's Speech and Language Development","year":2015,"lang":"en","type":"dissertation","venue":"TSpace (University of Toronto)","topic":"Education Systems and Policy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Linguistics; Computer science; Speech recognition; Psychology; Natural language processing; Philosophy","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":[0.02368028,0.0008173839,0.0007884169,0.002697219,0.001630993,0.00145874,0.001496449,0.0008963759,0.001586038],"category_scores_gemma":[0.04413206,0.0004621109,0.0005425494,0.002081472,0.001352789,0.001973741,0.001570603,0.0009168115,0.0005299988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002519379,"about_ca_system_score_gemma":0.009500724,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1157824,"about_ca_topic_score_gemma":0.2833585,"domain_scores_codex":[0.9843521,0.009283694,0.0008461744,0.001026291,0.004074381,0.0004173905],"domain_scores_gemma":[0.9789466,0.006441768,0.003922008,0.002451539,0.007520029,0.0007180984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003440786,0.0007088652,0.6800377,0.002073636,0.0002589735,0.0005003136,0.02419138,0.0008816582,0.005859395,0.001266276,0.001346547,0.2825312],"study_design_scores_gemma":[0.00008530297,0.004330723,0.9375315,0.001822679,0.0003888736,0.0008205827,0.02734378,0.001718981,0.007122306,0.0008745376,0.01776208,0.0001986159],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9271697,0.008364676,0.02994248,0.002563027,0.0004999863,0.004581894,0.001380581,0.0001737994,0.02532375],"genre_scores_gemma":[0.7777813,0.009711257,0.1985086,0.0009555159,0.000206759,0.006287996,0.0007825149,0.00003724354,0.005728819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8842176,"threshold_uncertainty_score":0.2302169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02238412904295657,"score_gpt":0.383610812216495,"score_spread":0.3612266831735385,"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."}}