{"id":"W6980427918","doi":"","title":"Career development of second-generation immigrant women","year":2010,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Career development; Population; Occupational prestige; Order (exchange)","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":[0.0008004199,0.0001883876,0.0001997718,0.0007054184,0.00331995,0.001173595,0.000239881,0.0005032548,0.001577355],"category_scores_gemma":[0.001308993,0.0001359447,0.0002259239,0.0004535014,0.0006879127,0.0004372431,0.001665256,0.0004584289,0.0002017849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00115888,"about_ca_system_score_gemma":0.00192958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02730598,"about_ca_topic_score_gemma":0.07196736,"domain_scores_codex":[0.9997082,0.00009036416,0.000009184433,0.00002242184,0.00003275952,0.0001370473],"domain_scores_gemma":[0.9994659,0.0001031971,0.00007071832,0.00001403403,0.00009895621,0.0002471471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001950613,0.0001859239,0.4449462,0.000154845,0.00001211308,0.005463725,0.5048857,0.00006529893,0.003948215,0.001195366,0.001813715,0.0371339],"study_design_scores_gemma":[0.00001001851,0.0003784534,0.3114004,0.000147702,0.000008330029,0.002659546,0.6695912,0.00009859703,0.0003435004,0.0001731959,0.01515669,0.00003247093],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976178,0.0003020997,0.00002131408,0.0001599418,0.00001013499,0.00000858609,0.00001810578,0.000001260924,0.001860835],"genre_scores_gemma":[0.9967526,0.000617827,0.0001085519,0.0001457546,0.000004825082,0.00001853876,0.00003978511,0.000001361821,0.002310748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02730598,"threshold_uncertainty_score":0.05429411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05171144893380696,"score_gpt":0.289983792548559,"score_spread":0.238272343614752,"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."}}