{"id":"W2219750714","doi":"10.5595/idrim.2015.0110","title":"Measuring Progress on Climate Change Adaptation: Lessons from the Community Well-Being Analogue","year":2015,"lang":"en","type":"article","venue":"IDRiM Journal","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Resources Canada; Wilfrid Laurier University","keywords":"Adaptation (eye); Scale (ratio); Climate change; Psychological resilience; Mainstreaming; Environmental resource management; Resilience (materials science); Environmental planning; Process management; Political science; Business; Environmental science; Geography; Psychology; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002175827,0.00008100023,0.00009221813,0.00004340988,0.002004256,0.000424829,0.0006155319,0.00003704312,0.00004052486],"category_scores_gemma":[0.0001018965,0.00005438627,0.00005161136,0.000183932,0.0002275379,0.0004049342,0.00010466,0.0004287259,0.00008662147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007574238,"about_ca_system_score_gemma":0.00005257231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001459425,"about_ca_topic_score_gemma":0.00575488,"domain_scores_codex":[0.9980178,0.0008420676,0.0001498153,0.00008423922,0.0006096109,0.0002965058],"domain_scores_gemma":[0.9993117,0.000134473,0.000137137,0.0001663366,0.00009914683,0.0001512312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000114255,0.0003336236,0.08923731,0.00001230839,0.0001022213,0.00008764683,0.6064,0.0003067796,0.000008650725,0.06545466,0.006925575,0.231017],"study_design_scores_gemma":[0.001593551,0.0002802601,0.2127083,0.0007898093,0.0001360259,0.00001239655,0.5854459,0.0009613812,0.0000379642,0.03711011,0.1603614,0.0005628323],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.761369,0.0006218975,0.000260971,0.02737925,0.001650023,0.0003068884,0.000005181026,0.00007623729,0.2083305],"genre_scores_gemma":[0.998011,0.0002063042,0.0001349366,0.0004734899,0.001013229,0.000007526854,0.000002406619,0.000006561041,0.0001445544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.236642,"threshold_uncertainty_score":0.999295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2686003855813774,"score_gpt":0.3648593328253579,"score_spread":0.09625894724398049,"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."}}