{"id":"W4398862989","doi":"10.7910/dvn/zbrtjh/ausinj","title":"Table2Sim3k.R","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Replication (statistics); Inference; Root (linguistics); Unit root; Computer science; Econometrics; Mathematics; Statistics; Artificial intelligence; Philosophy; Linguistics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002449521,0.00366964,0.002424383,0.003926666,0.001372505,0.004282057,0.005981163,0.002924474,0.2740695],"category_scores_gemma":[0.02323689,0.001248036,0.00248722,0.005694252,0.0008768766,0.001933992,0.002726572,0.002844227,0.2017938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001590299,"about_ca_system_score_gemma":0.003364642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01400567,"about_ca_topic_score_gemma":0.02634494,"domain_scores_codex":[0.9982886,0.0004156688,0.0001852155,0.0006197352,0.000287927,0.0002029153],"domain_scores_gemma":[0.9916213,0.004842805,0.0004796252,0.001718269,0.0008432116,0.0004948568],"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":[0.00005414449,0.0000153891,0.0003800786,0.0007379563,0.00005757202,0.00001716885,0.00001505984,0.0002838879,0.00004511507,0.0005562368,0.9966394,0.001198027],"study_design_scores_gemma":[0.001046021,0.0000298801,0.001879571,0.000601575,0.000133399,0.0001007156,0.00006234227,0.001112368,0.0004866307,0.008427166,0.9860563,0.00006404273],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008927716,0.00007854517,0.0002317975,0.00009672661,0.00003084774,0.00001730948,0.9973979,0.001287115,0.0007704452],"genre_scores_gemma":[0.001036851,0.0001199407,0.001223086,0.0002042441,0.00002377581,0.000340052,0.9948009,0.001103838,0.001147292],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7259305,"threshold_uncertainty_score":0.9168538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03057224920142849,"score_gpt":0.2574310480528469,"score_spread":0.2268587988514184,"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."}}