{"id":"W4398316758","doi":"10.7910/dvn/ii5jzg/ygev8d","title":"MSP_F_50_NFL_4_18.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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002497955,0.003349956,0.002818104,0.004755841,0.001638072,0.004478507,0.005223128,0.003261965,0.5166066],"category_scores_gemma":[0.01558387,0.001576391,0.001810837,0.006795513,0.001124212,0.003002778,0.003953015,0.002284352,0.4098498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001729835,"about_ca_system_score_gemma":0.003415615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01198219,"about_ca_topic_score_gemma":0.01667383,"domain_scores_codex":[0.9981124,0.0003296663,0.0002269669,0.0005310059,0.0003749879,0.0004248473],"domain_scores_gemma":[0.9944685,0.002305292,0.0004279835,0.00109974,0.001186749,0.0005117263],"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":[0.00006183037,0.00001800651,0.0002815193,0.0007966527,0.00002381742,0.00001461419,0.00003153514,0.0001049273,0.000119979,0.0004288266,0.9967766,0.001341688],"study_design_scores_gemma":[0.0007424326,0.00003532003,0.002123669,0.0005124739,0.00004322486,0.00006561859,0.00008886751,0.0002961538,0.0008641774,0.002817989,0.9923357,0.00007433732],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006627749,0.00003213852,0.0001266149,0.00006700064,0.00002833438,0.00002078354,0.9973904,0.001399169,0.0008693317],"genre_scores_gemma":[0.0007744337,0.00007424867,0.001075808,0.0001813744,0.00002590637,0.0005375866,0.9939628,0.001602483,0.001765363],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4833934,"threshold_uncertainty_score":0.689502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01698973672041462,"score_gpt":0.2370692565404349,"score_spread":0.2200795198200203,"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."}}