{"id":"W3126033693","doi":"10.2196/25935","title":"Collaborating in the Time of COVID-19: The Scope and Scale of Innovative Responses to a Global Pandemic","year":2021,"lang":"en","type":"review","venue":"JMIR Public Health and Surveillance","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"World Health Organization","keywords":"Crowdsourcing; Pandemic; Citizen science; Data sharing; Data science; Public relations; Knowledge management; Computer science; Political science; Coronavirus disease 2019 (COVID-19); World Wide Web; Medicine","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03122401,0.0005830675,0.0005697379,0.002357104,0.01017605,0.01815769,0.002060768,0.005868868,0.008122262],"category_scores_gemma":[0.04515131,0.0005709053,0.001130778,0.001896322,0.01129188,0.01937873,0.01767367,0.00592268,0.001447322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003820093,"about_ca_system_score_gemma":0.008633148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002237739,"about_ca_topic_score_gemma":0.003188819,"domain_scores_codex":[0.981358,0.01201405,0.000603058,0.00164606,0.002089252,0.0022896],"domain_scores_gemma":[0.9453467,0.03682378,0.002516465,0.004571188,0.004166151,0.006575603],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005225154,0.0002279881,0.02309115,0.002514372,0.0002012226,0.003321777,0.2305348,0.002863903,0.004877912,0.2016808,0.101755,0.4284085],"study_design_scores_gemma":[0.00004848237,0.0002523412,0.01085609,0.002701624,0.0001049748,0.0008459852,0.1732235,0.001223135,0.001345351,0.1219358,0.6873206,0.0001420852],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.2883667,0.03898475,0.04008209,0.3432537,0.00745439,0.0005752324,0.0005690119,0.0008007993,0.2799133],"genre_scores_gemma":[0.9408895,0.01320852,0.01694541,0.01672163,0.001359398,0.0004644998,0.0002650477,0.000293582,0.009852366],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.968776,"threshold_uncertainty_score":0.1651303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1048307138557685,"score_gpt":0.4581145811613143,"score_spread":0.3532838673055458,"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."}}