{"id":"W4411303057","doi":"10.2196/75025","title":"Analyzing Public Google Search Interest in Measles Within Canada: Identifying Key Moments for Targeted Risk Communication","year":2025,"lang":"en","type":"article","venue":"Journal of Medical Internet Research","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Preprint; Key (lock); World Wide Web; Internet privacy; Computer science; Public health; Data science; Computer security; Medicine; Nursing","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":[],"consensus_categories":[],"category_scores_codex":[0.0007393291,0.0002437712,0.0003025733,0.004662559,0.001400922,0.002338149,0.0006989304,0.0003712504,0.002323058],"category_scores_gemma":[0.007024403,0.0001336852,0.0003416302,0.009948284,0.0005804819,0.0009235141,0.00120346,0.0006595238,0.0004134662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01172362,"about_ca_system_score_gemma":0.01928611,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9517047,"about_ca_topic_score_gemma":0.9713788,"domain_scores_codex":[0.9990854,0.00007402046,0.00008103123,0.00008691568,0.0003370633,0.0003356189],"domain_scores_gemma":[0.994162,0.0009596766,0.002011115,0.0001382359,0.002097072,0.0006317689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001548125,0.00003689272,0.9690635,0.000337436,0.00005847793,0.000208231,0.004090641,0.0003520299,0.0003105631,0.0005714865,0.007061855,0.01775414],"study_design_scores_gemma":[0.000004098761,0.00001611126,0.9833512,0.000145876,0.00003409976,0.0001061975,0.009843596,0.001057514,0.0002430653,0.00009749079,0.0050836,0.00001721443],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9611932,0.001750394,0.0003297994,0.001856891,0.00003364176,0.0001013838,0.02496048,0.00009195012,0.009682229],"genre_scores_gemma":[0.9933259,0.0007448579,0.0004406034,0.0001548807,0.00001798295,0.00002789428,0.004084945,0.00001278393,0.001190108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04829526,"threshold_uncertainty_score":0.09715933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1561065882305097,"score_gpt":0.4449183468121169,"score_spread":0.2888117585816073,"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."}}