{"id":"W2304175625","doi":"10.1038/nclimate2841","title":"Roadmap towards justice in urban climate adaptation research","year":2016,"lang":"en","type":"article","venue":"Nature Climate Change","topic":"Climate Change, Adaptation, Migration","field":"Social Sciences","cited_by":602,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Climate justice; Adaptation (eye); Disadvantaged; Vulnerability (computing); Equity (law); Climate change; Political science; Transformative learning; Environmental planning; Adaptive capacity; Environmental justice; Empirical research; Globe; Climate change adaptation; Environmental resource management; Sociology; Geography; Economics; Psychology","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":[0.005352275,0.0002534715,0.000294366,0.0007109019,0.0009035143,0.0001684569,0.0004810511,0.0007729972,0.0004891765],"category_scores_gemma":[0.001493239,0.0002084444,0.00009080159,0.001523058,0.0003471444,0.001243232,0.0001497863,0.0007042074,0.000460234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001137904,"about_ca_system_score_gemma":0.0001806212,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001672739,"about_ca_topic_score_gemma":0.06710605,"domain_scores_codex":[0.9951447,0.0008993949,0.0004662529,0.0006651455,0.001390612,0.00143393],"domain_scores_gemma":[0.9976718,0.000718286,0.0002018635,0.0003904871,0.0007837344,0.000233773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006452824,0.0005835539,0.03223219,0.0006539891,0.00003147832,0.0001115319,0.4957832,0.00000494863,0.006083904,0.2923074,0.0129523,0.1586103],"study_design_scores_gemma":[0.005437904,0.0006151621,0.2825387,0.002563625,0.0001907391,0.00001078525,0.2811661,0.001184408,0.001355245,0.01032982,0.4122843,0.002323225],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8553452,0.005353794,0.0001071097,0.04573703,0.005188959,0.003637995,0.00059836,0.0007633297,0.08326818],"genre_scores_gemma":[0.9811515,0.0141007,0.0003775885,0.000625967,0.002722183,0.0003557605,0.00009989226,0.00005750554,0.0005088974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.399332,"threshold_uncertainty_score":0.9499168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3064058140514489,"score_gpt":0.4353314193575088,"score_spread":0.1289256053060599,"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."}}