{"id":"W6982625930","doi":"","title":"Investing in people : creating a human capital society for Ontario","year":2004,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Human capital; Government (linguistics); Capital (architecture); Investment (military); Work (physics)","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000332006,0.0003052961,0.0004798851,0.00007743053,0.0001097863,0.00004390656,0.0001612754,0.0003850707,0.07341538],"category_scores_gemma":[0.0002564036,0.0003277682,0.0002732597,0.0000107575,0.00004954038,4.063517e-7,0.00004814589,0.0002565251,0.0002839776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003362607,"about_ca_system_score_gemma":0.0001028323,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1716909,"about_ca_topic_score_gemma":0.536354,"domain_scores_codex":[0.9983362,0.00002506965,0.0008669234,0.0001916671,0.0002946552,0.0002854595],"domain_scores_gemma":[0.9984955,0.0002056848,0.000866689,0.0002422421,0.0001202701,0.00006961966],"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":[0.00001375344,0.0000556499,0.0001694478,0.001300207,0.00004123924,0.000001360484,0.003925283,0.0005131218,3.065076e-7,0.001695444,0.9921076,0.0001766098],"study_design_scores_gemma":[0.001013924,0.0000788008,0.0002110468,0.0007735749,0.00006499742,0.00001728402,0.0002411324,0.00008704988,0.000002080538,0.001773884,0.9953981,0.0003381314],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.005102579,0.00003871445,0.000008915352,0.00004964211,0.0001090597,0.0009061743,0.00007170034,0.0001420532,0.9935712],"genre_scores_gemma":[0.004450342,0.000005742714,0.02726667,0.00007352524,0.000125528,0.00004828378,0.0003890294,0.0001326093,0.9675083],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3646631,"threshold_uncertainty_score":0.9999174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01801318917109717,"score_gpt":0.2372353837372246,"score_spread":0.2192221945661274,"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."}}