{"id":"W4398458902","doi":"10.7910/dvn/ii5jzg/tmb32e","title":"MSP_F_150_NFL_4_3.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":"Materials science","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":[0.002402307,0.003420891,0.002938501,0.004670896,0.001635579,0.004632323,0.005353068,0.003400317,0.5262658],"category_scores_gemma":[0.01539863,0.001611264,0.001869021,0.006636918,0.001150425,0.003041717,0.004111932,0.002309792,0.4139467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00170512,"about_ca_system_score_gemma":0.003376021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01165371,"about_ca_topic_score_gemma":0.01611929,"domain_scores_codex":[0.998185,0.0003098338,0.0002138692,0.0005153947,0.0003586691,0.00041725],"domain_scores_gemma":[0.9945449,0.00226004,0.0004260224,0.001088693,0.001161974,0.0005184274],"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":[0.00006278535,0.0000180974,0.000281891,0.0008162701,0.0000248534,0.00001511884,0.00003187602,0.0001082005,0.0001186959,0.0004236458,0.9967573,0.001341382],"study_design_scores_gemma":[0.0007936906,0.00003750407,0.002087159,0.0005157526,0.00004588412,0.00006963895,0.00009067426,0.0003218025,0.0008914546,0.003139478,0.9919285,0.00007851709],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006798397,0.00003456874,0.0001332892,0.00007248273,0.00003019971,0.00002170134,0.9972254,0.001533513,0.0008809429],"genre_scores_gemma":[0.000840996,0.00007970667,0.001138739,0.0002034799,0.00002968034,0.0005791287,0.9934777,0.001770002,0.001880617],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4737342,"threshold_uncertainty_score":0.6757243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01689064407718472,"score_gpt":0.237007039740327,"score_spread":0.2201163956631423,"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."}}