{"id":"W3184777722","doi":"10.31532/interdiscipeducpsychol.3.1.001","title":"Planning for Teacher Recovery from the COVID-19 Pandemic: Adaptive Regulation to Promote Resilience","year":2021,"lang":"en","type":"article","venue":"Interdisciplinary Education and Psychology","topic":"Resilience and Mental Health","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Pandemic; Burnout; Resilience (materials science); Psychological resilience; Coronavirus disease 2019 (COVID-19); Construct (python library); Psychology; Diversity (politics); Political science; Public relations; Social psychology; Medicine; Computer science; Clinical psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003935612,0.0001333987,0.0001576101,0.00007044769,0.0003413146,0.00003000688,0.000188656,0.0001377625,0.000692093],"category_scores_gemma":[0.00009662935,0.0001069266,0.00005124238,0.0001862681,0.0001048491,0.00009759232,0.0001114839,0.0001771895,0.00008272686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001097236,"about_ca_system_score_gemma":0.0002599426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009254427,"about_ca_topic_score_gemma":0.0001491417,"domain_scores_codex":[0.9984936,0.0002576282,0.000293649,0.0006093086,0.00008109595,0.0002647009],"domain_scores_gemma":[0.9988377,0.0003341655,0.0001133742,0.0004308609,0.00006336207,0.0002205049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001994238,0.0006690302,0.04556892,0.00001908374,0.00006321296,0.000008289204,0.09166691,0.00003245608,0.001909853,0.001736845,0.3945461,0.461785],"study_design_scores_gemma":[0.001107303,0.001177355,0.6153947,0.0001143361,0.00004214034,0.0006227746,0.05996527,0.00006652843,0.00005767638,0.05725808,0.2638465,0.0003473673],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9276356,0.001499269,0.01838074,0.03443388,0.003310654,0.000760755,0.00004431413,0.00004645925,0.01388833],"genre_scores_gemma":[0.9567168,0.00003067737,0.002023066,0.02610693,0.0006040211,0.0004768804,0.0001406354,0.00001974997,0.01388121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5698258,"threshold_uncertainty_score":0.7577934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1031691877202959,"score_gpt":0.5043040045824135,"score_spread":0.4011348168621177,"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."}}