{"id":"W6958900940","doi":"10.6084/m9.figshare.5915032","title":"Parsing Science - Electoral Systems and Female Candidates","year":2018,"lang":"en","type":"other","venue":"Figshare","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Parsing; Politics; Term (time); Conjunction (astronomy); Context (archaeology)","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":[],"consensus_categories":[],"category_scores_codex":[0.001861722,0.00034498,0.0004171298,0.002437008,0.001646419,0.003359641,0.0004977474,0.0005184959,0.03106237],"category_scores_gemma":[0.01072081,0.0003591969,0.0004443048,0.004979656,0.001099028,0.002114812,0.002100186,0.0009171855,0.006669832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002300938,"about_ca_system_score_gemma":0.002088532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05552113,"about_ca_topic_score_gemma":0.1371159,"domain_scores_codex":[0.9988272,0.0003712636,0.00005680733,0.0003410791,0.0002251507,0.0001785191],"domain_scores_gemma":[0.9955117,0.002599137,0.0004598525,0.0005468843,0.0005786228,0.000303731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005681969,0.0001496656,0.3493691,0.0004320285,0.0001086326,0.0005475135,0.009807235,0.002234875,0.002661348,0.1429396,0.1834262,0.3077556],"study_design_scores_gemma":[0.00004235691,0.00004151544,0.2796151,0.0001879239,0.00004782833,0.000265047,0.008411708,0.005099843,0.002505379,0.1012395,0.6024755,0.00006822665],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5307704,0.00742388,0.08666677,0.02103639,0.000607729,0.0001729567,0.118655,0.002921538,0.2317454],"genre_scores_gemma":[0.8542175,0.001080516,0.01883096,0.0006048458,0.0002375489,0.0001229063,0.06121414,0.001327323,0.06236427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05552113,"threshold_uncertainty_score":0.1103959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03782068528138043,"score_gpt":0.2465105504759441,"score_spread":0.2086898651945636,"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."}}