{"id":"W6981889166","doi":"","title":"Frame Switching &amp;amp; Attributions - All Biculturals","year":2016,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Situational ethics; Frame (networking); Sample (material); Attribution; Replicate; Priming (agriculture)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002039091,0.0009081544,0.0007376152,0.0006632869,0.002396792,0.002043746,0.0009303249,0.0005260234,0.04640527],"category_scores_gemma":[0.0189616,0.0003209799,0.0004251297,0.0008311357,0.001391468,0.001792179,0.002199745,0.001772775,0.004846145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002016498,"about_ca_system_score_gemma":0.00198652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0958362,"about_ca_topic_score_gemma":0.1012812,"domain_scores_codex":[0.9987925,0.0002014809,0.00005862958,0.0003422611,0.0003633254,0.0002417987],"domain_scores_gemma":[0.9900687,0.002538078,0.001205186,0.003318535,0.001793727,0.001075681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01204315,0.00281233,0.4451264,0.001523722,0.0005733864,0.0009407627,0.05778563,0.001089454,0.09272222,0.01989369,0.05709801,0.3083914],"study_design_scores_gemma":[0.0002515391,0.0005088368,0.9291121,0.0001584354,0.0002687485,0.000401318,0.007025214,0.0007858497,0.01876646,0.007396849,0.03517766,0.0001469439],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9391257,0.0002684172,0.002289733,0.0004514828,0.0002144237,0.0002969977,0.005023137,0.0005606344,0.05176951],"genre_scores_gemma":[0.9779575,0.0001073507,0.001842954,0.0002735325,0.00004752952,0.0003237461,0.002329801,0.0003704064,0.01674707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0958362,"threshold_uncertainty_score":0.1905567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0364907436443125,"score_gpt":0.3118610453303191,"score_spread":0.2753703016860066,"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."}}