{"id":"W2964379774","doi":"10.2196/14056","title":"The SMART Framework: Integration of Citizen Science, Community-Based Participatory Research, and Systems Science for Population Health Science in the Digital Age","year":2019,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":114,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Canadian Institutes of Health Research","keywords":"Citizen science; Big data; Participatory action research; Conceptualization; Citizen journalism; Population; Population health; Sociology; Grand Challenges; Digital health; Data science; Community-based participatory research; Health equity; Public relations; Knowledge management; Computer science; Political science; Health care; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.01701704,0.00009701543,0.0001627859,0.0001978645,0.003510044,0.0004506362,0.000637672,0.00003921235,0.00002139103],"category_scores_gemma":[0.0003537908,0.0000605337,0.00001439526,0.002130863,0.00522297,0.0004384172,0.0001703489,0.0003906581,0.000007031965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009084473,"about_ca_system_score_gemma":0.0005718804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002362867,"about_ca_topic_score_gemma":0.0007215202,"domain_scores_codex":[0.9971218,0.0001996124,0.0003838176,0.000327454,0.001109959,0.0008574092],"domain_scores_gemma":[0.9984518,0.0005119301,0.0001958025,0.0004497484,0.00009209201,0.0002985772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002709397,0.0005414585,0.6963511,0.001172212,0.000001156757,5.453993e-7,0.0141303,0.0000470661,0.001151028,0.2611275,0.0007177549,0.02448898],"study_design_scores_gemma":[0.0002877665,0.000566457,0.9777456,0.00007267363,0.000001221071,0.0000021409,0.01576938,0.002383907,0.00002305927,0.001457206,0.001619983,0.00007058964],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947717,0.00009398785,0.00003514188,0.001844272,0.0001572215,0.001370339,0.00003169986,0.00001235054,0.001683281],"genre_scores_gemma":[0.999111,0.00006633871,0.00003952255,0.0006176272,0.00001239211,0.0001067848,0.00001796037,0.000004869072,0.00002351548],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2813945,"threshold_uncertainty_score":0.9977872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2617641767488845,"score_gpt":0.4544792821347042,"score_spread":0.1927151053858197,"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."}}