{"id":"W2156863109","doi":"10.1503/cmaj.080512","title":"Making early childhood count","year":2009,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Early Childhood Education and Development","field":"Social Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Early childhood; Computer science; Data science; Medicine; Developmental psychology; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008453668,0.000861354,0.0009865955,0.002717378,0.004515667,0.008132325,0.002341584,0.006707465,0.02651221],"category_scores_gemma":[0.0453415,0.0004445041,0.0005298008,0.001281521,0.01695674,0.01752941,0.01127809,0.01545227,0.006963235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004319615,"about_ca_system_score_gemma":0.00649686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01483428,"about_ca_topic_score_gemma":0.02824898,"domain_scores_codex":[0.9945235,0.002188782,0.000343709,0.0006745419,0.001586708,0.0006827125],"domain_scores_gemma":[0.9892126,0.004630045,0.0006045098,0.001046309,0.00268518,0.001821287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008072099,0.0000390957,0.002501147,0.0002811455,0.00003313453,0.000449536,0.003638608,0.0002021817,0.0001297236,0.4674884,0.3606141,0.1645421],"study_design_scores_gemma":[0.00001039793,0.00002123571,0.0008988587,0.001236095,0.00002451235,0.0002965247,0.003198991,0.00007258532,0.0001851773,0.1722901,0.8217406,0.00002484175],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.004237709,0.03399125,0.013869,0.7824507,0.03421862,0.00004758047,0.0004343168,0.0002207434,0.1305301],"genre_scores_gemma":[0.2747461,0.1303378,0.03392505,0.357688,0.05739151,0.0004477863,0.00135511,0.0009288477,0.1431797],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02651221,"threshold_uncertainty_score":0.08869219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01161802673759224,"score_gpt":0.2796414567348461,"score_spread":0.2680234299972539,"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."}}