{"id":"W6959138358","doi":"10.7910/dvn/ejqcxp","title":"Replication Data for: Gender Cues, Attributions and Stereotyping of Transgender and Nonbinary Politicians","year":2025,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Plant pathogens and resistance mechanisms","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Transgender; Attribution; Replication (statistics); Syntax; Replicate","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":[0.00592866,0.001177153,0.001155777,0.001930454,0.001356929,0.001777073,0.003260416,0.001623344,0.1035911],"category_scores_gemma":[0.03558835,0.0007536006,0.001160032,0.003968778,0.000499209,0.001184878,0.00222822,0.00229271,0.05788396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001910681,"about_ca_system_score_gemma":0.004203631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04239844,"about_ca_topic_score_gemma":0.07377806,"domain_scores_codex":[0.9969548,0.0008292144,0.0005221806,0.000681649,0.000669255,0.0003428776],"domain_scores_gemma":[0.9804595,0.004686207,0.002251492,0.005708893,0.00600414,0.0008899044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001339826,0.0000321861,0.003742316,0.0002972029,0.00004003513,0.0000179392,0.00006994599,0.0001099006,0.00007426352,0.0007166818,0.9923146,0.002450937],"study_design_scores_gemma":[0.0009656339,0.00006232897,0.04260492,0.0005979791,0.0001291314,0.0001134796,0.0004832903,0.0005011506,0.0007058701,0.002838073,0.950914,0.00008410741],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007371106,0.00002452835,0.0002311318,0.0001337115,0.00004786105,0.00005820243,0.9973845,0.000137231,0.001245664],"genre_scores_gemma":[0.003558219,0.00003283222,0.001179094,0.0001582159,0.00002343059,0.0009983884,0.989546,0.0001669313,0.004337023],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1035911,"threshold_uncertainty_score":0.3465466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06385193852688573,"score_gpt":0.2724022000767509,"score_spread":0.2085502615498651,"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."}}