{"id":"W4405722029","doi":"10.23977/jaip.2024.070410","title":"Analysis of the Impact of Machine Learning Research Methods on Labour Market Research—An Example from CNKI","year":2024,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Practice","topic":"Medical Research and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Data science; Manufacturing engineering; Engineering management; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03751193,0.0005553603,0.0008567154,0.01062649,0.001775093,0.004692356,0.001032613,0.0009604883,0.004084734],"category_scores_gemma":[0.08536014,0.0002381047,0.0009399058,0.01827105,0.00171329,0.004741353,0.001879245,0.002188672,0.0009702256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008530341,"about_ca_system_score_gemma":0.007398191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02097705,"about_ca_topic_score_gemma":0.02060533,"domain_scores_codex":[0.9823886,0.008448196,0.0008324062,0.000969737,0.006807684,0.0005533985],"domain_scores_gemma":[0.854745,0.1101306,0.006804003,0.005428505,0.02160115,0.001290729],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005079308,0.0002977415,0.1191453,0.003337459,0.0004508217,0.0006228357,0.005555405,0.00873832,0.001726735,0.1796526,0.01625836,0.6637065],"study_design_scores_gemma":[0.00007730322,0.0005023167,0.5652261,0.005882238,0.000550231,0.0009101743,0.01323538,0.06335468,0.007060712,0.102214,0.2407358,0.0002511935],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3780427,0.1658258,0.1793533,0.06444857,0.001947458,0.0007696474,0.004374119,0.0005950659,0.2046434],"genre_scores_gemma":[0.867707,0.04641237,0.06713139,0.002049012,0.0009360443,0.0002928558,0.001439948,0.0002047788,0.01382676],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9624881,"threshold_uncertainty_score":0.1983844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4543887770802889,"score_gpt":0.6298436124041137,"score_spread":0.1754548353238248,"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."}}