{"id":"W4392577319","doi":"10.5194/egusphere-egu24-12643","title":"Active demographic data collection in geoscience: results, implications, and recommendations from a survey of Canadian academia &amp;#160;","year":2024,"lang":"en","type":"preprint","venue":"","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Toronto","funders":"","keywords":"Geography; Earth science; Data science; Data collection; Geology; Computer science; Sociology; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0100153,0.000263474,0.0005019447,0.005522025,0.0002407297,0.0004352898,0.00169419,0.0007723427,0.0001171881],"category_scores_gemma":[0.006679759,0.0002297711,0.00007102296,0.0081767,0.0002058103,0.0003091238,0.00138912,0.001516514,0.00002858942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001118062,"about_ca_system_score_gemma":0.001476238,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8369812,"about_ca_topic_score_gemma":0.971394,"domain_scores_codex":[0.9946525,0.0007289284,0.001655515,0.001844371,0.0007841449,0.0003345796],"domain_scores_gemma":[0.9935444,0.002905171,0.0005848907,0.002000824,0.0006915935,0.0002731119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003386657,0.000223389,0.3428122,0.00006630847,0.0002873837,0.000002745167,0.006306903,0.001307678,0.0002228656,0.003760016,0.2678662,0.3768056],"study_design_scores_gemma":[0.0002187431,0.00001317251,0.8436521,0.0001407862,0.00004406229,0.000001850277,0.000786737,0.04561154,0.000005043441,0.1030963,0.006167735,0.000261933],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8928004,0.001826514,0.008626001,0.03152282,0.001628806,0.001285565,0.05477477,0.0001165523,0.007418594],"genre_scores_gemma":[0.970542,0.005692492,0.01048545,0.0002083805,0.00003318031,0.00007216571,0.01204185,0.00002294697,0.0009015355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5008398,"threshold_uncertainty_score":0.9369794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3912666118593737,"score_gpt":0.4510345542976023,"score_spread":0.05976794243822858,"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."}}