{"id":"W4398568300","doi":"10.7910/dvn/ii5jzg/fryijn","title":"MSP_F_50_NFL_4_32.xlsx","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Physics","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":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003783911,0.0005974229,0.0007550937,0.0003590491,0.0001660548,0.0008352686,0.008668289,0.0003246094,0.009063851],"category_scores_gemma":[0.00043306,0.0005842762,0.0002736494,0.001000878,0.000106815,0.001567748,0.00485126,0.0007916968,0.7131702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001065601,"about_ca_system_score_gemma":0.0003426629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003209306,"about_ca_topic_score_gemma":0.0001351392,"domain_scores_codex":[0.9959676,0.0001877054,0.0006126775,0.001579728,0.001030796,0.0006215342],"domain_scores_gemma":[0.9927222,0.0001229556,0.0004282804,0.006138181,0.0001043027,0.0004840477],"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":[0.000006964717,0.00005825891,0.000001328566,0.00007161165,0.0001583559,0.0005799645,0.00001488499,0.000004606424,0.000006073318,0.0004250578,0.9978361,0.0008368297],"study_design_scores_gemma":[0.0002991362,0.00005279934,0.000009056123,0.00004437771,0.0001816213,0.00003134292,0.000006894651,0.000943379,0.00001792152,0.0000767636,0.9976999,0.0006368337],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[1.434376e-7,0.000001535655,0.01554659,0.00007795475,0.001017767,0.0002204656,0.9825792,0.0002670526,0.0002892546],"genre_scores_gemma":[0.000001005377,0.0002454018,0.008980525,0.003247338,0.0004380845,0.00002606237,0.9867794,0.00002540495,0.0002567633],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7041063,"threshold_uncertainty_score":0.9996608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01701250023279021,"score_gpt":0.237103589966024,"score_spread":0.2200910897332338,"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."}}