{"id":"W2907738398","doi":"10.1016/j.eswa.2018.12.054","title":"Ranking résumés automatically using only résumés: A method free of job offers","year":2018,"lang":"fr","type":"article","venue":"Expert Systems with Applications","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"Consejo Nacional de Ciencia y Tecnología; Association Nationale de la Recherche et de la Technologie","keywords":"Ranking (information retrieval); Computer science; Relevance (law); Rank (graph theory); Information retrieval; Similarity (geometry); Job analysis; Vocabulary; Selection (genetic algorithm); Process (computing); Learning to rank; Resource (disambiguation); Artificial intelligence; Machine learning; Mathematics; Linguistics; Job satisfaction","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":[0.001484338,0.001883915,0.001845907,0.005625961,0.001112016,0.002825028,0.00220683,0.001353794,0.02823857],"category_scores_gemma":[0.009490781,0.0008216814,0.001200529,0.003653091,0.0004001645,0.003634417,0.002012118,0.001422303,0.02449211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003297363,"about_ca_system_score_gemma":0.00181562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00213444,"about_ca_topic_score_gemma":0.005563223,"domain_scores_codex":[0.9981336,0.000266526,0.000171305,0.0005037031,0.0007815406,0.0001433166],"domain_scores_gemma":[0.9941683,0.002287792,0.000354006,0.001537954,0.001290834,0.0003611542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001204078,0.0003951316,0.002801002,0.0005730352,0.0001572934,0.000223232,0.0001943115,0.001941652,0.0213053,0.002845657,0.07307483,0.8952845],"study_design_scores_gemma":[0.0008424144,0.0009493775,0.01979786,0.0003071655,0.0007279761,0.002264124,0.0008524201,0.5282019,0.100792,0.03699915,0.307739,0.0005266131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02279022,0.001427182,0.7724781,0.0004426725,0.0007018218,0.0007292422,0.0129336,0.1767385,0.01175874],"genre_scores_gemma":[0.1544648,0.0005147258,0.7524502,0.0002276907,0.0006539366,0.0005541154,0.01986594,0.01060187,0.06066673],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02823857,"threshold_uncertainty_score":0.0944674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05402005072200111,"score_gpt":0.3750287497506595,"score_spread":0.3210086990286584,"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."}}