{"id":"W3113159769","doi":"10.3390/su122410589","title":"Paying Attention: Big Data and Social Advertising as Barriers to Ecological Change","year":2020,"lang":"en","type":"article","venue":"Sustainability","topic":"Death Anxiety and Social Exclusion","field":"Psychology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Commodification; Advertising; Social media; Sustainability; Commodity; Big data; Consumption (sociology); Business; Space (punctuation); Marketing; Sociology; Economics; Ecology; Social science; World Wide Web; Economy; Computer 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005427661,0.0001236675,0.0002043883,0.0000225632,0.0006096748,0.00004165685,0.0002771174,0.000179137,0.0005830884],"category_scores_gemma":[0.001680217,0.0001215845,0.0000557483,0.0002250122,0.0001485799,0.000137996,0.000746228,0.0002091181,0.00005170995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001770247,"about_ca_system_score_gemma":0.0001497058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003109815,"about_ca_topic_score_gemma":0.00004705734,"domain_scores_codex":[0.9984217,0.0002651683,0.000194859,0.000605814,0.0001314814,0.000381007],"domain_scores_gemma":[0.9990826,0.00006502597,0.00004271799,0.0002962078,0.0001384398,0.0003749669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00081816,0.0002016095,0.2501879,0.0003034782,0.00006765228,0.000218077,0.1177097,6.035009e-7,0.00005979632,0.01811812,0.01037152,0.6019433],"study_design_scores_gemma":[0.0008191657,0.0003589128,0.7472052,0.000004471362,0.0000447324,0.000005690296,0.06214413,0.00006815785,0.000002056752,0.009451036,0.1795613,0.0003351498],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9214809,0.00009500378,0.0003105665,0.07508802,0.0004422996,0.0006065663,0.00003314471,0.0001022052,0.001841292],"genre_scores_gemma":[0.988482,0.000003905594,0.00003600772,0.01039436,0.0008203501,0.00003869105,0.00003269612,0.00001064305,0.0001813724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6016082,"threshold_uncertainty_score":0.6384408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08744330466122559,"score_gpt":0.3650392783995758,"score_spread":0.2775959737383502,"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."}}