{"id":"W4366312296","doi":"10.2139/ssrn.4409857","title":"Storms, Early Education and Human Capital","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; Université de Sherbrooke; Université de Montréal","funders":"","keywords":"Human capital; Storm; Deskilling; Cohort; Demographic economics; Geography; Climate change; Demography; Socioeconomics; Economics; Economic growth; Medicine; Sociology; Engineering; Meteorology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001551964,0.00006577207,0.00006701524,0.000154339,0.0009081443,0.0001366596,0.0001051343,0.00005610945,0.00003734653],"category_scores_gemma":[0.00007954738,0.00006699761,0.00003057614,0.0002885814,0.00007142709,0.0003965624,0.0000118207,0.0004079948,0.00006742965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008903499,"about_ca_system_score_gemma":0.002030756,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00454469,"about_ca_topic_score_gemma":0.1100478,"domain_scores_codex":[0.9984544,0.00009355434,0.0001349462,0.00011396,0.0002685149,0.0009346457],"domain_scores_gemma":[0.9996345,0.00003151709,0.00009466978,0.00005611878,0.0001050899,0.00007812653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000543408,0.00004551078,0.02084511,0.000003629119,0.00002633253,6.849559e-7,0.05258273,0.000002156908,0.0008737224,0.896382,0.0007686701,0.02846405],"study_design_scores_gemma":[0.000329366,0.0002196075,0.1133627,0.00002096628,0.00002813259,0.00003015968,0.227266,0.00001103501,0.00002266233,0.6473585,0.0111278,0.0002231584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950077,0.0006537567,0.00006962144,0.001726094,0.0002897969,0.0001053164,0.000001116728,0.00006892269,0.002077665],"genre_scores_gemma":[0.9874883,0.002898298,0.00001322519,0.00003490524,0.0007028714,0.000007207899,0.00001395184,0.00001133235,0.008829964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2490235,"threshold_uncertainty_score":0.9061915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04368035049591846,"score_gpt":0.3275085143880132,"score_spread":0.2838281638920948,"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."}}