{"id":"W7103290719","doi":"","title":"PrÃ©cieux et convoitÃ© comme des diamants: Le Nanny Angel Network de Toronto","year":2016,"lang":"en","type":"article","venue":"PubMed Central","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Reflection (computer programming); 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":[0.002480288,0.0006908262,0.0005511243,0.002006757,0.007406744,0.006436443,0.000860516,0.001844549,0.1170932],"category_scores_gemma":[0.005271738,0.0004698889,0.0003468437,0.003248897,0.002143478,0.001930837,0.002760448,0.002354599,0.01170625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04809673,"about_ca_system_score_gemma":0.1160459,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8675721,"about_ca_topic_score_gemma":0.9380217,"domain_scores_codex":[0.9977762,0.0002765923,0.0001086929,0.0001971552,0.0009727752,0.0006686519],"domain_scores_gemma":[0.9947102,0.0004517663,0.0002728479,0.000164836,0.001881568,0.002518693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00005931828,0.000007829053,0.001022884,0.0003573562,0.000009509687,0.0003218082,0.001574634,0.00008733885,0.0002194729,0.02316564,0.9392756,0.03389865],"study_design_scores_gemma":[0.000004671721,0.00000386096,0.002302162,0.0001143125,0.000003113955,0.00004137667,0.0007746419,0.00001636325,0.00005888892,0.000264807,0.9964094,0.000006323311],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01311001,0.170342,0.001191933,0.2536753,0.02738572,0.0001815239,0.01122138,0.0006577593,0.5222343],"genre_scores_gemma":[0.07632446,0.04573896,0.001222305,0.004459623,0.001739762,0.00009701224,0.002169766,0.0002522356,0.8679958],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1324279,"threshold_uncertainty_score":0.3917157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02836053326234006,"score_gpt":0.242731080220643,"score_spread":0.2143705469583029,"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."}}