{"id":"W1582774710","doi":"10.1111/j.1749-6632.2009.05308.x","title":"Chapter 1: New York City adaptation in context","year":2010,"lang":"en","type":"article","venue":"Annals of the New York Academy of Sciences","topic":"Climate Change and Environmental Impact","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Climate change; Context (archaeology); Environmental planning; Sustainability; Flooding (psychology); Urban resilience; Greenhouse gas; Environmental resource management; Political science; Adaptation (eye); Urban planning; Geography; Engineering; Environmental science; Civil engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005957364,0.000116113,0.0001632934,0.00004599505,0.0001010766,0.00001534321,0.0007304919,0.00009318173,0.001872769],"category_scores_gemma":[0.00005499497,0.0000787157,0.00008797493,0.0003596524,0.0009512415,0.0003153174,0.0001968856,0.0002136784,0.000067997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001094516,"about_ca_system_score_gemma":0.00001110819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00459442,"about_ca_topic_score_gemma":0.001066801,"domain_scores_codex":[0.9987094,0.00002282938,0.0002798198,0.0002411179,0.0004753979,0.0002713713],"domain_scores_gemma":[0.9994714,0.0000655672,0.0002258811,0.0001053118,0.000001366426,0.0001305005],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00009665663,0.0002159733,0.2916511,0.00001432728,0.00001724628,4.386117e-7,0.01375536,0.00291791,0.4008073,0.002570499,0.04659352,0.2413597],"study_design_scores_gemma":[0.0003994658,0.0001619687,0.72069,0.00008988906,0.0000107522,0.000005789564,0.001764036,0.0007031017,0.2336621,0.02014486,0.02210404,0.0002640228],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9819536,0.0002256788,0.000005951715,0.01213275,0.0001024108,0.0001422982,0.000005260866,0.000006454424,0.005425611],"genre_scores_gemma":[0.996995,0.0001081083,0.0003213546,0.001708251,0.00005360441,0.000001112449,2.663367e-7,0.000004732951,0.0008075355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4290389,"threshold_uncertainty_score":0.9990396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1962747894749065,"score_gpt":0.3324648018926903,"score_spread":0.1361900124177838,"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."}}