{"id":"W4399011409","doi":"10.7910/dvn/s0yzu3","title":"Replication Data for: The pandemic’s effects on publishing at Politics &amp; Gender","year":2023,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Gender Politics and Representation","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Replication (statistics); Politics; Pandemic; Publishing; Political science; Sociology; Virology; Biology; Coronavirus disease 2019 (COVID-19); Medicine; Law; Internal 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002632199,0.0002287092,0.0002222298,0.0001351812,0.001409778,0.000833373,0.002751638,0.0004121863,0.0003615561],"category_scores_gemma":[0.009144262,0.0001807085,0.00009699079,0.0002235835,0.000186991,0.0006275547,0.001319062,0.0004053679,0.02684342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003768509,"about_ca_system_score_gemma":0.0003806673,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01481608,"about_ca_topic_score_gemma":0.01333793,"domain_scores_codex":[0.9969658,0.0003160095,0.0003178826,0.0009348599,0.0008485605,0.0006168541],"domain_scores_gemma":[0.991073,0.002389493,0.0002940559,0.005895631,0.0001523059,0.0001955703],"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":[0.000008400089,0.00002085646,0.00003106702,0.0001126665,0.00009085512,0.000002355216,0.0003901228,0.000006789647,0.00000252827,0.002838518,0.9961087,0.000387199],"study_design_scores_gemma":[0.0002423094,0.000009411772,0.0002341082,0.00003249229,0.0002189642,0.000001463496,0.0006384101,0.00004549868,0.000002547156,0.001393097,0.9969676,0.0002141448],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001926312,0.000004210633,0.0001670854,0.0004268138,0.002291885,0.001044985,0.9952807,0.0001125666,0.0006524536],"genre_scores_gemma":[0.00004006004,0.001216721,0.00008679578,0.00116235,0.002514758,0.0001123225,0.9903604,0.00003347249,0.004473129],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02648186,"threshold_uncertainty_score":0.9998903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1766715162858829,"score_gpt":0.3876185010012872,"score_spread":0.2109469847154043,"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."}}