{"id":"W6969013082","doi":"10.5683/sp2/djnpqv","title":"Inoculating against an infodemic: microlearning interventions to address CoV misinformation","year":2021,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Roads University","funders":"Canadian Institutes of Health Research","keywords":"Misinformation; Psychological intervention; Protocol (science); Pandemic; Set (abstract data type); Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.003554133,0.0008938007,0.0007668125,0.004901648,0.002191272,0.002133967,0.002993624,0.001341695,0.05950975],"category_scores_gemma":[0.01740704,0.0006125071,0.001090968,0.008287675,0.000570397,0.001035329,0.0031091,0.001478874,0.0168962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009033609,"about_ca_system_score_gemma":0.01358642,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5602429,"about_ca_topic_score_gemma":0.7898228,"domain_scores_codex":[0.9978435,0.0007378652,0.0002215356,0.000251625,0.000617891,0.0003276486],"domain_scores_gemma":[0.9902281,0.0033118,0.0007856398,0.00130455,0.003610524,0.0007595024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001588745,0.00004971368,0.003538148,0.002409466,0.00005411376,0.00003643911,0.0007741052,0.0003796633,0.0001367008,0.001604711,0.9797149,0.01114313],"study_design_scores_gemma":[0.0003863025,0.0000480469,0.02077074,0.001790893,0.00007498864,0.00004173886,0.002211662,0.000533105,0.0003783293,0.001250199,0.9724385,0.00007544256],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009228033,0.0001115036,0.0001320666,0.0002554516,0.00002538936,0.0001756629,0.995402,0.0001472662,0.002827857],"genre_scores_gemma":[0.005936094,0.0002186919,0.001751869,0.0002174794,0.00001441851,0.002535561,0.9856551,0.0001263202,0.003544411],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5602429,"threshold_uncertainty_score":0.8846939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04919762360633011,"score_gpt":0.3461050459942728,"score_spread":0.2969074223879427,"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."}}