{"id":"W4213241381","doi":"10.1016/j.joi.2022.101256","title":"Female inventors over time: Factors affecting female Inventors’ innovation performance","year":2022,"lang":"en","type":"article","venue":"Journal of Informetrics","topic":"Innovation Policy and R&D","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"HEC Montréal","keywords":"Business; Production (economics); European patent office; Panel data; Demographic economics; Industrial organization; Economics; International trade; Microeconomics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002513051,0.0001740323,0.0004145639,0.004160278,0.0004223343,0.0000936272,0.0003673964,0.00009485387,0.001135823],"category_scores_gemma":[0.001075487,0.0001813779,0.0001618812,0.007234946,0.00003610332,0.00107486,0.0001495089,0.0006463935,0.00009102733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005711061,"about_ca_system_score_gemma":0.0001137765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003488643,"about_ca_topic_score_gemma":5.826487e-7,"domain_scores_codex":[0.9975646,0.00002020818,0.001697088,0.0001450004,0.0002429056,0.0003301851],"domain_scores_gemma":[0.9966962,0.000114311,0.002685862,0.0001913587,0.0002425259,0.00006971365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000508724,0.000175095,0.9418544,0.00008826686,0.0001191308,0.000005170022,0.003987478,0.002249709,0.00006256653,0.04150205,0.007762387,0.002142913],"study_design_scores_gemma":[0.003370756,0.001894378,0.5782592,0.00006794091,0.00003253742,0.0001418477,0.003262587,0.005646558,0.003259467,0.003487182,0.3994334,0.001144102],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848,0.0001922441,0.0003334201,0.00008556531,0.001439454,0.0001215431,0.00004693774,0.00001794896,0.01296287],"genre_scores_gemma":[0.996564,0.00005362384,0.000313246,0.0007563661,0.0002736002,0.00000325775,0.00002596528,0.00002428253,0.001985641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.391671,"threshold_uncertainty_score":0.9997773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0561466103949233,"score_gpt":0.2499877970366727,"score_spread":0.1938411866417494,"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."}}