{"id":"W2750691521","doi":"10.36510/learnland.v10i2.813","title":"smartEducation: Developing Stress Management and Resiliency Techniques","year":2017,"lang":"en","type":"article","venue":"LEARNing Landscapes","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mindfulness; Variety (cybernetics); Stress management; Medical education; Psychological resilience; Psychology; Curriculum; Professional development; Resilience (materials science); Face (sociological concept); Pedagogy; Applied psychology; Medicine; Clinical psychology; Psychotherapist; Sociology; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0001824911,0.0000852946,0.00009467918,0.0000661287,0.0006202887,0.00009382176,0.0001581672,0.00004934722,0.0001961823],"category_scores_gemma":[0.00002444403,0.00007829216,0.00001565364,0.00003024921,0.0000313289,0.00008393231,0.00009295039,0.0001332293,0.00005693635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004044588,"about_ca_system_score_gemma":0.00003059187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003604156,"about_ca_topic_score_gemma":0.0001500581,"domain_scores_codex":[0.9993187,0.00004831086,0.0001149333,0.0002391618,0.0000796411,0.0001992333],"domain_scores_gemma":[0.9995158,0.00004347623,0.0001015783,0.0002712666,0.00001551731,0.00005237644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002913315,0.00003806879,0.7012621,0.0001658248,0.00002477335,0.00001841111,0.002402088,7.812767e-7,0.00001360943,0.01141195,0.001380481,0.2832528],"study_design_scores_gemma":[0.0002236186,0.00005879211,0.7844483,0.0001142369,0.00001031113,0.000007099824,0.001342931,0.000008969992,0.0001198218,0.0002931309,0.2132591,0.0001137069],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8404266,0.0008850306,0.0007287889,0.002843891,0.0005282019,0.0003067562,0.000002106495,0.0002216472,0.1540569],"genre_scores_gemma":[0.9830982,0.0002546357,0.001387065,0.0002003174,0.0001302182,0.00004967567,0.000009170989,0.0000116714,0.01485902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2831391,"threshold_uncertainty_score":0.4770822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03903875021491111,"score_gpt":0.3942769864106134,"score_spread":0.3552382361957023,"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."}}