{"id":"W4233576972","doi":"10.26434/chemrxiv-2021-5d9tt-v2","title":"Gender Distribution and Geography of Highly Cited Papers in ACS Catalysis","year":2021,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Distribution (mathematics); Geography; Regional science; Economic geography; Political science; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.008632581,0.0006452897,0.001048503,0.02034311,0.001454719,0.008163901,0.0007255345,0.0008099546,0.02120657],"category_scores_gemma":[0.04104142,0.0002919312,0.0009505257,0.0285871,0.001031536,0.002486492,0.00215135,0.0006806101,0.006242966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001823325,"about_ca_system_score_gemma":0.001924269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001864711,"about_ca_topic_score_gemma":0.002693019,"domain_scores_codex":[0.9910834,0.001841649,0.001295544,0.001489434,0.003332024,0.0009578391],"domain_scores_gemma":[0.9535711,0.01945894,0.009463407,0.002503041,0.0114037,0.003599754],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002741537,0.0002018874,0.3182679,0.01161389,0.002048186,0.003056485,0.007412442,0.001636007,0.01750904,0.0343989,0.2779033,0.3232104],"study_design_scores_gemma":[0.00009284962,0.0002827087,0.3995568,0.001820886,0.0006034363,0.001958674,0.006345432,0.0008450617,0.007291448,0.01338867,0.5676337,0.0001803303],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4688926,0.2168052,0.01040445,0.0309425,0.02021767,0.0004634731,0.1024864,0.001197485,0.1485903],"genre_scores_gemma":[0.837337,0.06118646,0.006875558,0.003279288,0.007549717,0.0004383082,0.02923405,0.0009374567,0.05316212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9913674,"threshold_uncertainty_score":0.07094312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008574701960843966,"score_gpt":0.2077167457203915,"score_spread":0.1991420437595475,"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."}}