{"id":"W798571909","doi":"10.51644/jjbc4581","title":"Remembering for the Future","year":2012,"lang":"en","type":"article","venue":"Consensus","topic":"Oral History, Memory, Narrative Analysis","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Computer science; Epistemology; Philosophy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001748093,0.00008668652,0.0001104336,0.00003372841,0.0005293276,0.00003630736,0.00009189853,0.00002251845,0.001372776],"category_scores_gemma":[0.00004166325,0.00005560113,0.000110186,0.0000225315,0.0001995834,0.0000449903,0.00001329814,0.00007055265,0.0001326172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003246079,"about_ca_system_score_gemma":0.0000150969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003722356,"about_ca_topic_score_gemma":0.0008152984,"domain_scores_codex":[0.9994844,0.00002605723,0.0001149125,0.00008688711,0.0000794686,0.0002082511],"domain_scores_gemma":[0.9994474,0.0001664452,0.00005215359,0.0002017291,0.00008767039,0.00004460013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005664832,0.00005985615,0.0005456991,0.00004207259,0.0002339339,0.000002340692,0.06702552,0.000005435247,0.0003890413,0.198026,0.7091961,0.02441729],"study_design_scores_gemma":[0.0001165386,0.00001338863,0.0001247097,0.000003256159,0.00007662446,0.000001714394,0.01578,0.00006125445,0.000112667,0.0001563554,0.9834644,0.00008910543],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3050041,0.1040077,0.0002482573,0.02908001,0.0274449,0.001715938,0.0001873345,0.0005037767,0.531808],"genre_scores_gemma":[0.9502183,0.00001861875,0.0001141687,0.0004708808,0.006183822,0.00002975127,0.000003811665,0.0000174445,0.04294324],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6452141,"threshold_uncertainty_score":0.9995401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05915590876016463,"score_gpt":0.26008804600694,"score_spread":0.2009321372467754,"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."}}