{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1021992,0.002614671,0.003191743,0.01164658,0.008628794,0.01905911,0.006370108,0.01011003,0.009822418],"category_scores_gemma":[0.05544134,0.001548514,0.004306467,0.009048809,0.04880792,0.02455585,0.03525285,0.01440394,0.002572467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01422749,"about_ca_system_score_gemma":0.05362706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01175289,"about_ca_topic_score_gemma":0.01997499,"domain_scores_codex":[0.8661526,0.1151987,0.002898856,0.005475484,0.008035536,0.002238896],"domain_scores_gemma":[0.9312009,0.04859483,0.00203537,0.008406458,0.004403613,0.005358905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004377856,0.0001037521,0.00101695,0.001688909,0.0001287523,0.00021863,0.01193517,0.001197022,0.0002918422,0.8861836,0.01939915,0.07779247],"study_design_scores_gemma":[0.00003835573,0.00006516651,0.000613764,0.002511765,0.00006354569,0.000152146,0.004303883,0.001825994,0.0001680662,0.7880339,0.2021663,0.00005709066],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003711188,0.02050066,0.6743076,0.1743276,0.004362828,0.002696442,0.001240162,0.001773134,0.1170804],"genre_scores_gemma":[0.07509506,0.01130891,0.8794122,0.01801166,0.001279315,0.006190777,0.001130929,0.0005531274,0.007017997],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1021992,"threshold_uncertainty_score":0.5404873,"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."}}