{"id":"W4375858460","doi":"10.54932/houf2464","title":"Storms, Early Education and Human Capital","year":2023,"lang":"en","type":"report","venue":"","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; Université de Sherbrooke","funders":"Social Sciences and Humanities Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Human capital; Storm; Deskilling; Geography; Cohort; Demographic economics; Climate change; Socioeconomics; Demography; Economic growth; Economics; Medicine; Meteorology; Sociology; Engineering; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001891607,0.00009312728,0.00008437721,0.000589172,0.0003229518,0.0008256225,0.0001605579,0.000183315,0.002879567],"category_scores_gemma":[0.001504299,0.0000532143,0.0001113669,0.0008537939,0.0003967423,0.0002992504,0.0005906814,0.0002653909,0.0001929904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006043657,"about_ca_system_score_gemma":0.0008137562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03207874,"about_ca_topic_score_gemma":0.05214404,"domain_scores_codex":[0.9998184,0.00003359656,0.000009202559,0.00001462072,0.00003109065,0.00009311361],"domain_scores_gemma":[0.9986386,0.0002712759,0.00055918,0.00004938002,0.00008151286,0.0004000577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005714635,0.0001113171,0.9809797,0.00003082385,0.00003673884,0.0002206631,0.0004430483,0.0005705163,0.0001629734,0.001418471,0.0006041816,0.01536435],"study_design_scores_gemma":[0.000001407205,0.00003252137,0.9974809,0.00001503187,0.000006808195,0.00008239665,0.000433121,0.000109618,0.00005519544,0.0005235045,0.001257075,0.000002411702],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912874,0.000702888,0.00009378912,0.0005668288,0.00001079359,0.000006062718,0.000471912,0.00000459597,0.006855833],"genre_scores_gemma":[0.9987597,0.0003326257,0.00003216227,0.00002671123,0.000007079406,0.000001524736,0.00008942498,3.993146e-7,0.0007505033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03207874,"threshold_uncertainty_score":0.06378406,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04534289962404859,"score_gpt":0.2984290178598248,"score_spread":0.2530861182357763,"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."}}