{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008503295,0.0002009722,0.0001535948,0.0009774221,0.005029471,0.003079116,0.0006845898,0.0006801245,0.01868748],"category_scores_gemma":[0.002440153,0.0001900928,0.0001984296,0.002608022,0.0008553645,0.001740381,0.001674988,0.0005517803,0.001371269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04546459,"about_ca_system_score_gemma":0.1464443,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9714793,"about_ca_topic_score_gemma":0.9934911,"domain_scores_codex":[0.9993772,0.00005430705,0.00002352652,0.00003554374,0.0002931992,0.0002163776],"domain_scores_gemma":[0.9974503,0.0001009768,0.0001347846,0.00008198934,0.000811542,0.001420395],"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":[0.0000528795,0.00009515523,0.07441822,0.0002844098,0.00001703001,0.0004061093,0.01808636,0.0006939186,0.0007950207,0.0499891,0.5954993,0.2596625],"study_design_scores_gemma":[0.00001415177,0.00003097315,0.08716767,0.0001004479,0.0000166894,0.00005255643,0.01076953,0.0004312004,0.0002304564,0.00362875,0.8975332,0.0000244003],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2846349,0.004856325,0.00452595,0.1517156,0.0008500873,0.0007452364,0.01140854,0.0004801487,0.540783],"genre_scores_gemma":[0.4146495,0.007450703,0.01369668,0.003138349,0.00015225,0.0002906913,0.003266273,0.000207417,0.5571482],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04546459,"threshold_uncertainty_score":0.3298702,"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."}}