{"id":"W4289522698","doi":"10.3390/healthcare10081451","title":"Use of Netnography to Understand GoFundMe® Crowdfunding Profiles Posted for Individuals and Families of Children with Osteogenesis Imperfecta","year":2022,"lang":"en","type":"article","venue":"Healthcare","topic":"Connective tissue disorders research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Shriners Hospitals for Children - Canada","funders":"","keywords":"Osteogenesis imperfecta; Netnography; Social media; Business; Marketing; Internet privacy; Variety (cybernetics); Psychology; Medicine; Public relations; Advertising; Political science; World Wide Web; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001753238,0.0001107552,0.0001893095,0.0001812642,0.0001730326,0.00001108424,0.000114928,0.00004891403,0.000009434936],"category_scores_gemma":[0.00008154096,0.0001081493,0.00004829013,0.000309767,0.00008471711,0.000004407788,0.0002061113,0.00006036301,5.648822e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001780377,"about_ca_system_score_gemma":0.0001263541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007481102,"about_ca_topic_score_gemma":0.0006330407,"domain_scores_codex":[0.9989852,0.0001216559,0.0001727878,0.000299836,0.0001846652,0.0002359018],"domain_scores_gemma":[0.9993801,0.00005766102,0.00008489707,0.0002247556,0.000170035,0.00008262214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005855786,0.00005020066,0.8535022,0.0002597063,0.0001401476,3.274245e-7,0.001084916,0.00004708535,0.1387383,0.0001574244,0.0002217444,0.005212318],"study_design_scores_gemma":[0.00215047,0.01166918,0.6607867,0.00008369981,0.00006530347,0.00003229424,0.01860941,0.0000205007,0.3037727,0.000102608,0.002219559,0.0004875905],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946297,0.002143401,0.000173456,0.000483765,0.00001481007,0.001273324,0.001268572,0.000005340348,0.000007592795],"genre_scores_gemma":[0.9986882,0.0001264766,0.0006083123,0.0000913965,0.00001282733,0.0001235735,0.0002997777,0.00002503481,0.00002442299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1927155,"threshold_uncertainty_score":0.4410201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04263257783625656,"score_gpt":0.3133142760156368,"score_spread":0.2706816981793802,"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."}}