{"id":"W3139755592","doi":"10.1016/j.bodyim.2021.04.002","title":"#quarantine15: A content analysis of Instagram posts during COVID-19","year":2021,"lang":"en","type":"article","venue":"Body Image","topic":"Obesity and Health Practices","field":"Health Professions","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Psychology; Content analysis; Social media; Content (measure theory); Stigma (botany); Coronavirus disease 2019 (COVID-19); Weight stigma; Social psychology; Body weight; Pandemic; Overweight; Body mass index; Medicine; Sociology; Psychiatry; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009830241,0.0001339111,0.000550534,0.0003081042,0.0009062547,0.00001518526,0.0001526018,0.0001591595,0.003913698],"category_scores_gemma":[0.002253429,0.0001279292,0.0001908481,0.00104903,0.00007249034,0.0002805637,0.000164283,0.0005357836,0.0003507418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001380624,"about_ca_system_score_gemma":0.001083679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002605126,"about_ca_topic_score_gemma":0.003904351,"domain_scores_codex":[0.9972887,0.0008425633,0.0007579514,0.0003222729,0.0002973644,0.0004911516],"domain_scores_gemma":[0.9972758,0.0009813283,0.0005269545,0.0004767623,0.0004172451,0.0003218717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006007578,0.0009533554,0.8855913,0.006970694,0.001654377,0.0005831366,0.01251345,0.00002530007,0.07702997,0.008781364,0.004986056,0.0003102859],"study_design_scores_gemma":[0.001753966,0.00004746136,0.9651659,0.00014059,0.0008442443,0.000004441576,0.008047206,0.0002631076,0.0008600128,0.00008404398,0.02260476,0.0001842613],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717203,0.0004290183,0.0004883372,0.008464383,0.0002474487,0.0004168504,0.0001332666,0.00009635592,0.01800408],"genre_scores_gemma":[0.9876989,0.0003793248,0.0009131775,0.004619779,0.0001136738,0.00003798516,0.00009314076,0.00001658874,0.006127453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07957465,"threshold_uncertainty_score":0.9969969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1349272040252742,"score_gpt":0.4871171585127041,"score_spread":0.3521899544874299,"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."}}