{"id":"W6888742788","doi":"10.21949/1527311","title":"Employee Assistance Program for Transit Systems","year":2015,"lang":"en","type":"report","venue":"Rosa P: A digital library for transportation research (United States Department of Transportation)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Glossary; Sample (material); Transit system; Public transport","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.002918748,0.001610585,0.002417458,0.003015678,0.000559093,0.001247464,0.001426886,0.001074249,0.0001032644],"category_scores_gemma":[0.000273628,0.001687541,0.001655735,0.004700944,0.000860723,0.004938995,0.000009048749,0.001107111,0.0000713959],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007919937,"about_ca_system_score_gemma":0.005967401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006823574,"about_ca_topic_score_gemma":0.0006760529,"domain_scores_codex":[0.9826447,0.0002544153,0.00411522,0.002219016,0.008390022,0.002376611],"domain_scores_gemma":[0.9823197,0.001678393,0.001777235,0.001194936,0.01177819,0.001251535],"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":[0.007817151,0.002885747,0.004271089,0.01708773,0.002733435,0.0001595592,0.001367065,0.004454332,0.000009330939,0.005116951,0.950743,0.00335464],"study_design_scores_gemma":[0.004988104,0.003489848,0.003066186,0.00141891,0.0008691482,0.000004140859,0.001305618,0.001024728,0.0003077796,0.002498505,0.9794613,0.001565694],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.04686237,0.002408734,0.006005988,0.0002894694,0.0007016417,0.02080806,0.9207633,0.001657439,0.0005029544],"genre_scores_gemma":[0.1044073,0.0009093489,0.004601337,0.00002689657,0.0003130859,0.01841947,0.8663573,0.001180266,0.003784951],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05754496,"threshold_uncertainty_score":0.9997894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09537430244129505,"score_gpt":0.365607800314847,"score_spread":0.2702334978735519,"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."}}