{"id":"W4387775653","doi":"10.2139/ssrn.4583322","title":"Make it Personal: Standardization and Prosocial Behavior","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Prosocial behavior; Standardization; Psychology; Social psychology; Internet privacy; Applied psychology; Computer science; Political science; Law","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":[0.005329828,0.0002546267,0.0002321745,0.001548884,0.002250381,0.004181829,0.0003661469,0.000958258,0.002825957],"category_scores_gemma":[0.02043818,0.0002236762,0.0002892808,0.0009810303,0.003465164,0.001775761,0.001684259,0.001565151,0.0002509759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007608997,"about_ca_system_score_gemma":0.0009828288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002332828,"about_ca_topic_score_gemma":0.002953558,"domain_scores_codex":[0.9974227,0.001320581,0.0001501547,0.0002064869,0.0006679709,0.0002320395],"domain_scores_gemma":[0.9753482,0.009642445,0.006852895,0.003144499,0.00192389,0.003088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002464628,0.001195303,0.7981402,0.00007168291,0.0002097955,0.0005618142,0.07079034,0.000526322,0.003943054,0.03051724,0.001327054,0.09247076],"study_design_scores_gemma":[0.00006056886,0.0004489681,0.8648829,0.00009684879,0.0001926562,0.001193298,0.08433754,0.002581234,0.001576215,0.03389055,0.01065347,0.00008584116],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982161,0.0001803989,0.001019701,0.0007351511,0.00003103005,0.00002152248,0.0000120858,0.0000145283,0.01582457],"genre_scores_gemma":[0.9990869,0.00003915843,0.0002472459,0.00004606486,0.000009739674,0.000004383305,0.000006938469,0.000005252307,0.0005543974],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005329828,"threshold_uncertainty_score":0.02818716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02300470056626976,"score_gpt":0.3442355623251756,"score_spread":0.3212308617589059,"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."}}