{"id":"W4301057346","doi":"10.21428/594757db.858dd91f","title":"“FIJO”: a French Insurance Soft Skill Detection Dataset","year":2022,"lang":"en","type":"article","venue":"","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Transformer; Artificial intelligence; Security token; Domain (mathematical analysis); Machine learning; Natural language processing","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":[0.0006913212,0.001007915,0.0005434635,0.003729849,0.0009213441,0.000782085,0.001334652,0.001745583,0.004942247],"category_scores_gemma":[0.001703893,0.0001521168,0.000867654,0.002509141,0.0003518235,0.0004790312,0.0007084146,0.0007754767,0.00350065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001995893,"about_ca_system_score_gemma":0.001734595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1290407,"about_ca_topic_score_gemma":0.1821796,"domain_scores_codex":[0.9993193,0.0001005295,0.0000625556,0.0001690173,0.0002102457,0.0001383058],"domain_scores_gemma":[0.9991369,0.0001840958,0.00007814571,0.0001329215,0.000319603,0.0001484063],"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":[0.0008164502,0.001093923,0.03790251,0.001045521,0.0002147085,0.001652376,0.0004349114,0.006890793,0.007567576,0.002943135,0.8491437,0.0902945],"study_design_scores_gemma":[0.0003402834,0.0003248002,0.2888404,0.0002766995,0.0000891485,0.001668764,0.001475316,0.03207899,0.007836876,0.001602507,0.6653093,0.0001569387],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.21508,0.00146368,0.003434501,0.001468446,0.0003160617,0.0003933584,0.7618081,0.003861292,0.01217455],"genre_scores_gemma":[0.08439772,0.0002908491,0.00639677,0.0002891223,0.0001023796,0.0002814418,0.9027132,0.0001258626,0.005402633],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1290407,"threshold_uncertainty_score":0.2565792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01248135543590495,"score_gpt":0.2062973154451216,"score_spread":0.1938159600092166,"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."}}