{"id":"W3094109472","doi":"10.17269/s41997-020-00432-0","title":"Neighbourhood climate resilience: lessons from the Lighthouse Project","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Public Health","topic":"Religion, Society, and Development","field":"Social Sciences","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Neighbourhood (mathematics); Emergency management; Stakeholder; Community resilience; Citizen journalism; Community organization; Public relations; Resilience (materials science); Disadvantaged; Local community; Environmental planning; Political science; Sociology; Geography; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003665614,0.0001018285,0.0002333895,0.00007439133,0.001539961,0.000398699,0.0006968041,0.00008641354,0.000159364],"category_scores_gemma":[0.001478441,0.00007281143,0.0001181157,0.0006944669,0.0002459568,0.0002915086,0.00001836486,0.0003764886,0.00002552374],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007079921,"about_ca_system_score_gemma":0.04265031,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4387554,"about_ca_topic_score_gemma":0.3735634,"domain_scores_codex":[0.9972907,0.0006905437,0.0004778008,0.0001606049,0.0004875953,0.0008927378],"domain_scores_gemma":[0.996475,0.0002071994,0.0003589395,0.0001350338,0.0002602663,0.002563519],"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":[0.000002143059,0.000009044425,0.01514932,0.000007160839,0.00002532792,0.00002331273,0.5003885,0.000002633439,8.550812e-7,0.007355178,0.4716622,0.005374365],"study_design_scores_gemma":[0.0002279655,0.00008345868,0.06537294,0.00003618453,0.000005352445,0.000005587648,0.193133,0.000008375762,0.000001003548,0.0009091689,0.7401046,0.0001123995],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2342674,0.008753909,0.000348101,0.7511851,0.0008633229,0.0002894828,0.00005832183,0.00002447675,0.004209842],"genre_scores_gemma":[0.9644925,0.01056976,0.0006677044,0.02299593,0.001231304,0.000002618351,0.000003194389,0.00001273855,0.00002426819],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.730225,"threshold_uncertainty_score":0.9997599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1137838144615177,"score_gpt":0.3631674732378883,"score_spread":0.2493836587763706,"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."}}