{"id":"W4328123480","doi":"10.1080/10848770.2023.2192069","title":"Windswept: Walking the Paths of Trailblazing Women","year":2023,"lang":"en","type":"article","venue":"The European Legacy","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001106754,0.0004147782,0.0002155818,0.0007048274,0.03170801,0.004755558,0.0006486134,0.00211017,0.01845336],"category_scores_gemma":[0.00262661,0.0003748451,0.0001964486,0.001089028,0.007600987,0.00323921,0.004997424,0.002926232,0.00261789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002389265,"about_ca_system_score_gemma":0.00403526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07057248,"about_ca_topic_score_gemma":0.2530321,"domain_scores_codex":[0.9989151,0.0005472443,0.00001768852,0.00007147779,0.00007810287,0.0003703351],"domain_scores_gemma":[0.99934,0.0001350867,0.00004786949,0.00004484207,0.00007695193,0.0003551587],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005441797,0.00004826943,0.003911286,0.00005495095,0.000004868949,0.0008657139,0.9011489,0.0000243868,0.0002831606,0.009426106,0.05435784,0.02982008],"study_design_scores_gemma":[0.000004631768,0.00001988501,0.001656635,0.0001068794,0.00000215133,0.0001144813,0.8161325,0.00001148242,0.00006496432,0.0008926736,0.1809864,0.000007221983],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6195421,0.003331851,0.001323503,0.05217422,0.001791896,0.0001001772,0.0002622304,0.0001391474,0.321335],"genre_scores_gemma":[0.8393056,0.002160116,0.001011191,0.00573783,0.0001071495,0.00006122322,0.0001162987,0.0001416073,0.1513589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07057248,"threshold_uncertainty_score":0.1403235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03332494213492689,"score_gpt":0.277103808188793,"score_spread":0.2437788660538661,"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."}}