{"id":"W4389045464","doi":"10.1038/s41561-023-01315-y","title":"Collaboration between women helps close the gender gap in ice core science","year":2023,"lang":"en","type":"article","venue":"Nature Geoscience","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Gender gap; Closing (real estate); Publishing; Core (optical fiber); Women in science; Ice core; Psychology; Political science; Sociology; Geology; Climatology; Demographic economics; Engineering; Gender studies; Economics; Telecommunications","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":["metaresearch","bibliometrics","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["metaresearch","bibliometrics"],"category_scores_codex":[0.07133667,0.0001841321,0.0002764529,0.04322385,0.001215698,0.004290005,0.007487312,0.0002481365,0.0001247144],"category_scores_gemma":[0.07683225,0.0001066419,0.00005998148,0.5819609,0.001519929,0.001881689,0.001629283,0.001031259,0.0007877941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004800214,"about_ca_system_score_gemma":0.001484011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006201863,"about_ca_topic_score_gemma":0.00006218021,"domain_scores_codex":[0.9790624,0.0002215213,0.0006450532,0.001451358,0.01703085,0.001588767],"domain_scores_gemma":[0.9896083,0.004796413,0.0002569525,0.001346034,0.003463193,0.0005290647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000263156,0.0000981191,0.8807662,0.000009177341,0.000004767208,0.00005276379,0.004454203,0.000271997,0.007475648,0.01739306,0.02469519,0.06475262],"study_design_scores_gemma":[0.0002408567,0.00007276505,0.9292003,0.000005314209,0.000001269378,0.000003436479,0.003387365,0.006530532,0.0003323318,0.0340619,0.02597385,0.0001900816],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892757,0.0003263603,0.0002155824,0.003892232,0.00133297,0.000421515,0.00005671796,0.00006229378,0.004416644],"genre_scores_gemma":[0.9963372,0.0000988731,0.0002233691,0.0006498508,0.0001502738,0.00003631596,0.000003303372,0.000008013873,0.002492755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.538737,"threshold_uncertainty_score":0.9999902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5513996505730159,"score_gpt":0.594976695241037,"score_spread":0.04357704466802115,"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."}}