{"id":"W4398831778","doi":"10.7910/dvn/s6b7se/f8hdfe","title":"R_Replication_File_PSLE.R","year":2020,"lang":"fa","type":"dataset","venue":"Harvard Dataverse","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Replication (statistics); Computer science; Biology; Database; Virology","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":["insufficient_payload"],"category_scores_codex":[0.005836944,0.003732274,0.003579413,0.004917379,0.001922272,0.005981393,0.006490747,0.00266346,0.3894243],"category_scores_gemma":[0.03473105,0.002462556,0.002609528,0.006580302,0.001310074,0.003399057,0.004200913,0.003118915,0.3352332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00145573,"about_ca_system_score_gemma":0.004150252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01096416,"about_ca_topic_score_gemma":0.0133841,"domain_scores_codex":[0.9964824,0.0008730097,0.0003617115,0.001161287,0.00068834,0.000433174],"domain_scores_gemma":[0.986375,0.006068701,0.0007446876,0.004135646,0.001986341,0.0006896752],"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":[0.00007862927,0.0000136303,0.0003950858,0.0009720848,0.000107415,0.00002067401,0.00004757636,0.0002404968,0.0001987418,0.001301006,0.9940441,0.002580623],"study_design_scores_gemma":[0.0006250896,0.00003023682,0.00171257,0.0004582308,0.0001478185,0.00009180658,0.00005136555,0.0006592823,0.001383446,0.008436939,0.9862871,0.0001162222],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001774932,0.0001521978,0.002118607,0.000199804,0.000108078,0.00007155034,0.9829078,0.01167566,0.002588799],"genre_scores_gemma":[0.003420231,0.0003057046,0.01001771,0.0005342267,0.00009086917,0.001644522,0.9602039,0.01887006,0.0049127],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6105757,"threshold_uncertainty_score":0.8709121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02338833170306331,"score_gpt":0.2521051184531842,"score_spread":0.2287167867501209,"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."}}