{"id":"W6925345840","doi":"10.17605/osf.io/nja63","title":"Happy climate framing for climate action - HSP study","year":2024,"lang":"en","type":"other","venue":"Open Science Framework","topic":"Synthetic Aperture Radar (SAR) Applications and Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Framing (construction); Climate change; Climate system; Climate justice; Climate science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005514732,0.0002332668,0.0002688335,0.0009016242,0.002533259,0.002776812,0.0005722697,0.0008485678,0.01441558],"category_scores_gemma":[0.01829172,0.0002041276,0.0003033604,0.0007528257,0.00147421,0.002510584,0.003030872,0.003130907,0.001207771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001414295,"about_ca_system_score_gemma":0.001502381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004441168,"about_ca_topic_score_gemma":0.006963057,"domain_scores_codex":[0.9964942,0.002246998,0.00006646088,0.0002284298,0.0004387933,0.0005251518],"domain_scores_gemma":[0.9801895,0.01092382,0.004816669,0.001066011,0.001021088,0.00198285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001201737,0.006483639,0.5830798,0.0003471508,0.0001797906,0.0009480683,0.1360214,0.0009747121,0.0007287193,0.1671703,0.01440928,0.08845536],"study_design_scores_gemma":[0.0001807477,0.001126969,0.5949109,0.0004451677,0.0002122457,0.0004906046,0.2848226,0.003765521,0.0009765392,0.04288508,0.07007289,0.0001107383],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9418884,0.0002041029,0.001147826,0.001923746,0.00008866796,0.00006856612,0.0002088019,0.000006920159,0.05446296],"genre_scores_gemma":[0.9962927,0.00009882179,0.0002107334,0.0003320744,0.00004545353,0.00006423903,0.00008133045,0.000006422822,0.002868246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01441558,"threshold_uncertainty_score":0.04822499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02957710848890915,"score_gpt":0.3613997124368579,"score_spread":0.3318226039479487,"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."}}