{"id":"W7015447857","doi":"","title":"Stories of Hungarians in Canada: Interviews","year":2012,"lang":"en","type":"other","venue":"University of Debrecen Electronic Archive (University of Debrecen)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Narrative; Ethnic group; Government (linguistics); Theme (computing)","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":[0.002673948,0.0008815419,0.0008140094,0.003796421,0.03922502,0.01210462,0.002512946,0.003462685,0.0147056],"category_scores_gemma":[0.01348943,0.0008729122,0.0002601788,0.01299132,0.01047148,0.003445963,0.007100875,0.004921796,0.001223926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08876732,"about_ca_system_score_gemma":0.09110729,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.959376,"about_ca_topic_score_gemma":0.9859155,"domain_scores_codex":[0.9957625,0.001127365,0.0001260631,0.0003038739,0.0006598723,0.002020282],"domain_scores_gemma":[0.9891236,0.004323823,0.0007012467,0.0001977018,0.002407097,0.003246604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005386687,0.00002567252,0.002509667,0.00006629367,0.000003632643,0.0009820211,0.9781195,0.00003209224,0.0002227983,0.001915882,0.01185932,0.004209223],"study_design_scores_gemma":[0.000002148761,0.000003732494,0.002892922,0.00008233279,0.000002197432,0.00005741877,0.959344,0.00001444621,0.0000676761,0.00009042583,0.03743216,0.00001049201],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8477665,0.004981504,0.000458258,0.01707099,0.0003118123,0.000265521,0.002693193,0.00004731345,0.126405],"genre_scores_gemma":[0.9422621,0.003370014,0.0004000225,0.003174576,0.00005606567,0.0001455629,0.0005479812,0.0001213751,0.04992231],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08876732,"threshold_uncertainty_score":0.644055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009471258551572947,"score_gpt":0.177985859821992,"score_spread":0.1685146012704191,"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."}}