{"id":"W3040609178","doi":"10.31646/gbio.80","title":"Unmasking reasons for face mask resistance","year":2020,"lang":"en","type":"article","venue":"Global Biosecurity","topic":"Textile materials and evaluations","field":"Materials Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Face (sociological concept); Resistance (ecology); Philosophy; Linguistics; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003288716,0.0005563502,0.0002530755,0.0008606181,0.001393739,0.002563594,0.001259313,0.002787432,0.01664472],"category_scores_gemma":[0.01379475,0.0002437004,0.000648908,0.0003823418,0.001837755,0.002417987,0.001387612,0.001965976,0.001901192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001271667,"about_ca_system_score_gemma":0.001156611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001166698,"about_ca_topic_score_gemma":0.001318169,"domain_scores_codex":[0.9953793,0.0008512545,0.0001234034,0.0004688645,0.00239879,0.0007783482],"domain_scores_gemma":[0.9925718,0.004068947,0.00106471,0.0009085043,0.001180508,0.0002055727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.002682074,0.0006500791,0.07361975,0.002095797,0.0002413749,0.01385724,0.01104593,0.003168612,0.2749138,0.1810168,0.02668272,0.4100258],"study_design_scores_gemma":[0.00009308634,0.001870228,0.1124849,0.001594799,0.0004969742,0.02229674,0.03436219,0.01124295,0.4574826,0.05316479,0.3046678,0.0002429079],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8165256,0.004348382,0.01356018,0.01154798,0.0009310792,0.0002645487,0.0001882103,0.0003058821,0.1523282],"genre_scores_gemma":[0.9879186,0.0004859028,0.0021187,0.0006072969,0.00008073296,0.00002308925,0.0000422663,0.00005398261,0.00866947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01664472,"threshold_uncertainty_score":0.05568212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03787374193956731,"score_gpt":0.29469286885097,"score_spread":0.2568191269114026,"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."}}