{"id":"W3124602252","doi":"10.2139/ssrn.2954242","title":"Seeking Resources: Predicting Retirees' Return to Their Workplace","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Business","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":[0.000895561,0.000318543,0.0002835498,0.001209874,0.0007995386,0.001079279,0.0005583671,0.001485602,0.00649514],"category_scores_gemma":[0.005484903,0.0002222686,0.0005567818,0.0006852663,0.0003073094,0.0007380571,0.0008730994,0.00118377,0.001160116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004033372,"about_ca_system_score_gemma":0.0007761277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02081881,"about_ca_topic_score_gemma":0.04313847,"domain_scores_codex":[0.999624,0.00008509871,0.00004217403,0.0000371375,0.00006033999,0.0001511868],"domain_scores_gemma":[0.9956261,0.001070333,0.001127735,0.000163982,0.0003481146,0.001663628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005967983,0.0001530677,0.9971872,0.000005487097,0.0000174654,0.00002209744,0.00009341173,0.00004941869,0.00002832674,0.00001554333,0.0001921738,0.002176069],"study_design_scores_gemma":[0.000006183713,0.0001023675,0.9981008,0.00001407966,0.00002080195,0.00004207985,0.001057651,0.0003409836,0.00002335995,0.00003935954,0.0002478168,0.000004559231],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987597,0.000137087,0.00002477879,0.0001990082,0.00001454239,0.000006464285,0.0002413524,0.000002505396,0.0006145408],"genre_scores_gemma":[0.9985287,0.0001140834,0.00004401445,0.00005371688,0.00001529686,0.000006227509,0.0003324764,0.00000121492,0.0009041361],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02081881,"threshold_uncertainty_score":0.04139525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07788791184561238,"score_gpt":0.360962165717311,"score_spread":0.2830742538716987,"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."}}