{"id":"W2166212864","doi":"","title":"Canadian Families in the Global Context: Data Challenges and Research Opportunities","year":2015,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Data science; Computer science; Geography","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01403676,0.0007979711,0.001169291,0.007510012,0.009762566,0.005764205,0.003592215,0.001000331,0.009398337],"category_scores_gemma":[0.04139274,0.0005073144,0.0007446379,0.03333778,0.002583453,0.002880309,0.003318356,0.001996671,0.0006139624],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06792827,"about_ca_system_score_gemma":0.1529437,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9971904,"about_ca_topic_score_gemma":0.9985541,"domain_scores_codex":[0.9921083,0.002271195,0.0003770996,0.0008401812,0.002680981,0.001722086],"domain_scores_gemma":[0.9618259,0.01015736,0.002089172,0.002806233,0.02054864,0.00257265],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004111267,0.0002401297,0.5252725,0.00175465,0.0007038444,0.0005507946,0.02168263,0.005691044,0.0005724242,0.05490433,0.2104774,0.177739],"study_design_scores_gemma":[0.000128913,0.00008603277,0.4683012,0.003254361,0.00047671,0.0003242712,0.09680819,0.007458674,0.001086171,0.02177375,0.3999235,0.0003781982],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.4791925,0.01964695,0.0267511,0.09386277,0.0016663,0.001751647,0.240465,0.0004488774,0.1362148],"genre_scores_gemma":[0.8856607,0.01487774,0.03778108,0.009241425,0.0003638588,0.001733063,0.03676966,0.0002395595,0.01333301],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9859632,"threshold_uncertainty_score":0.4928564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8195574597390738,"score_gpt":0.4900407085196485,"score_spread":0.3295167512194253,"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."}}