{"id":"W4409089311","doi":"10.1177/14614448251314401","title":"Tracking menopause: An SDK Data Audit for intimate infrastructures of datafication with ChatGPT4o","year":2025,"lang":"en","type":"article","venue":"New Media & Society","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Audit; Tracking (education); Menopause; Computer science; Business; Psychology; Process management; Accounting; Medicine","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":[0.01723275,0.0005378618,0.0004607007,0.005368417,0.002449284,0.00382306,0.001440069,0.0008306548,0.003551422],"category_scores_gemma":[0.08394796,0.0006090399,0.0004313325,0.004311823,0.002406484,0.006162911,0.007046412,0.001943342,0.001207874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002382512,"about_ca_system_score_gemma":0.006007157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00588823,"about_ca_topic_score_gemma":0.008505265,"domain_scores_codex":[0.9840872,0.00627424,0.001816124,0.001947674,0.005014806,0.0008600398],"domain_scores_gemma":[0.9179885,0.03099651,0.01502231,0.01799623,0.01559525,0.002401307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0008929507,0.0005114345,0.4971795,0.001156753,0.00009799165,0.001125212,0.07205511,0.001625896,0.008567092,0.02562548,0.0109115,0.3802511],"study_design_scores_gemma":[0.0002005798,0.001997771,0.5163809,0.002647927,0.000289786,0.002696742,0.09005795,0.03405007,0.03360486,0.04586317,0.2716869,0.0005234156],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7979026,0.0005651567,0.1490051,0.002074971,0.0003132518,0.005093434,0.004784886,0.003802699,0.03645797],"genre_scores_gemma":[0.8744741,0.0002624347,0.1107369,0.000545459,0.00007368466,0.003813802,0.002020817,0.0005424067,0.007530379],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01723275,"threshold_uncertainty_score":0.09113657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08922166399411123,"score_gpt":0.4122718701313975,"score_spread":0.3230502061372863,"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."}}