{"id":"W1499176806","doi":"","title":"Limitations of Canada's physical activity data: implications for monitoring trends.","year":2007,"lang":"en","type":"article","venue":"PubMed","topic":"Physical Activity and Health","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Confusion; Physical activity; Public health; Interpretation (philosophy); Public health surveillance; Data science; Medicine; Psychology; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.06884874,0.001084247,0.001388884,0.008339322,0.006251275,0.006167747,0.006984102,0.0009281964,0.002083949],"category_scores_gemma":[0.2361884,0.0006428846,0.0009336171,0.03272333,0.002082959,0.002503399,0.002656065,0.002199213,0.0003847569],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0538949,"about_ca_system_score_gemma":0.1839786,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9911344,"about_ca_topic_score_gemma":0.9913203,"domain_scores_codex":[0.9394997,0.01508093,0.007730413,0.00270628,0.03272701,0.00225564],"domain_scores_gemma":[0.7802809,0.0877822,0.02174898,0.008946978,0.09671035,0.004530616],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003381289,0.0001665897,0.5098109,0.005594247,0.0005928492,0.0004240504,0.01395999,0.005998191,0.0008228117,0.02032631,0.1808085,0.2611575],"study_design_scores_gemma":[0.0000826189,0.000115671,0.7981686,0.005860237,0.0005910707,0.0003951867,0.01625084,0.01212013,0.001650993,0.00804447,0.1564454,0.0002748452],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2035108,0.03745269,0.09681326,0.2819652,0.004724712,0.006477495,0.2622755,0.001736773,0.1050435],"genre_scores_gemma":[0.7694591,0.02102415,0.1198123,0.03126312,0.0008414204,0.004100276,0.04644573,0.0003585105,0.006695333],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9461051,"threshold_uncertainty_score":0.3910366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3158627307671095,"score_gpt":0.3790829567973194,"score_spread":0.06322022603020988,"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."}}