{"id":"W2232396140","doi":"","title":"Prolonging working lives in information technology employment","year":2006,"lang":"en","type":"other","venue":"Swinburne Research Bank (Swinburne University of Technology)","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Labour economics; Information technology; Public relations; Economics; Political science; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00235873,0.0001075816,0.0001516599,0.000630096,0.003417133,0.002197255,0.0003459395,0.0004232216,0.002070508],"category_scores_gemma":[0.005238795,0.0001122692,0.0001290907,0.0004331368,0.00198147,0.001428188,0.002667485,0.0007846943,0.0002038576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00128932,"about_ca_system_score_gemma":0.001738128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003428822,"about_ca_topic_score_gemma":0.008312853,"domain_scores_codex":[0.9988808,0.0004958643,0.00004598407,0.00007401532,0.0001615347,0.0003417858],"domain_scores_gemma":[0.9964339,0.001237804,0.0008202915,0.0001208973,0.000301528,0.001085624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001825216,0.0004956809,0.261702,0.0002334217,0.00002054368,0.0007599933,0.5781262,0.0002568561,0.002066808,0.007088272,0.002625377,0.1464422],"study_design_scores_gemma":[0.00001284588,0.0005135494,0.569746,0.0002779151,0.00001578716,0.0005148696,0.3854344,0.0001563727,0.0005671905,0.002576415,0.04014973,0.00003487181],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931105,0.0006111176,0.0001305961,0.0005528391,0.00001501484,0.000006544459,0.00001237991,0.000002405458,0.005558535],"genre_scores_gemma":[0.9980674,0.0003954795,0.0001064238,0.00009900244,0.000009893274,0.000007157188,0.00001245528,0.000001434969,0.001300764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003428822,"threshold_uncertainty_score":0.01247436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1080697593853896,"score_gpt":0.3794941072653742,"score_spread":0.2714243478799846,"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."}}