{"id":"W2099596552","doi":"","title":"Bootstrapping via Graph Propagation","year":2012,"lang":"en","type":"article","venue":"Summit (Simon Fraser University)","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Bootstrapping (finance); Computer science; Graph; Classifier (UML); Artificial intelligence; Theoretical computer science; Machine learning; Algorithm; Mathematics","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":[0.000163613,0.0001208016,0.0001014983,0.0002901543,0.0002200966,0.00005191285,0.0005375196,0.00006229185,0.00003248333],"category_scores_gemma":[0.00001158367,0.0001281216,0.0000717943,0.000818868,0.00003570788,0.001017336,0.0001446107,0.0001983981,0.000120922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004518533,"about_ca_system_score_gemma":0.0000241932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000824329,"about_ca_topic_score_gemma":0.0002300846,"domain_scores_codex":[0.9990628,0.00009109895,0.00008547298,0.0002364564,0.0001880651,0.0003360474],"domain_scores_gemma":[0.9993834,0.00003152977,0.00007020068,0.0003087382,0.00004503008,0.0001610329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001331431,0.0002017911,0.8763844,0.0000387578,0.0000556266,0.00007003173,0.0001515731,0.0007841529,0.0000916902,0.04022912,0.005455876,0.07652368],"study_design_scores_gemma":[0.002085049,0.0002589066,0.03558064,0.00008620279,0.00008197913,1.637374e-7,0.003132749,0.1306742,0.006062844,0.001974691,0.8185568,0.001505765],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07573863,0.00007341196,0.9100695,0.0004123003,0.0004620466,0.0001070193,0.000001210807,0.0003644359,0.01277143],"genre_scores_gemma":[0.9938671,0.000009476859,0.00386275,0.00009619306,0.0001223343,3.249171e-7,0.000005516095,0.000007031722,0.002029283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9181285,"threshold_uncertainty_score":0.5224648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01139237205410802,"score_gpt":0.2080648294632566,"score_spread":0.1966724574091486,"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."}}