{"id":"W4394023732","doi":"10.5281/zenodo.3950116","title":"The Many Faces of CI - Reproduction Package","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Multimedia Communication and Technology","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Reproduction; R package; Computer science; Biology; Programming language; Ecology","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":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001386842,0.0001112759,0.0001632467,0.000145575,0.004043211,0.0003836223,0.002706922,0.0001710842,0.006499491],"category_scores_gemma":[0.005651237,0.00009970831,0.00005735278,0.0006084549,0.0009772722,0.00009166481,0.001430086,0.0005227569,0.009304817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009465715,"about_ca_system_score_gemma":0.00001232846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002568165,"about_ca_topic_score_gemma":0.00001838508,"domain_scores_codex":[0.9977086,0.000951849,0.0002917837,0.0003415814,0.0004548625,0.0002512878],"domain_scores_gemma":[0.9978938,0.0001047661,0.0003039151,0.001132743,0.0004637873,0.0001009627],"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":[0.00001501981,0.00004136534,1.380972e-7,0.00002724597,0.00002600314,0.000001225157,0.0008024542,3.455521e-7,0.00005962175,0.004082848,0.9604046,0.03453917],"study_design_scores_gemma":[0.0001055827,0.00007146362,0.00001180343,0.00001601359,0.00001465301,0.000003970571,0.001453617,0.000005352769,0.00004922108,0.000231663,0.9979401,0.00009655152],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004744027,0.0003839976,0.0001048363,0.02408401,0.000406898,0.0009343358,0.9311447,0.0008910057,0.04200275],"genre_scores_gemma":[0.002465644,0.006407102,0.00009897496,0.00009638532,0.0003002587,1.114539e-7,0.9893733,0.0004284742,0.000829783],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05822855,"threshold_uncertainty_score":0.9972534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06005509694663862,"score_gpt":0.3082854806005167,"score_spread":0.2482303836538781,"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."}}