{"id":"W4398518012","doi":"10.7910/dvn/ii5jzg/f07hbj","title":"MSP_F_50_NFL_4_7.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":[0.0003721534,0.0005885151,0.0007445119,0.0003557716,0.0001646386,0.0008221869,0.008604468,0.0003211519,0.009003021],"category_scores_gemma":[0.000425601,0.000575517,0.0002731703,0.0009906967,0.0001070495,0.001492022,0.004844477,0.000780578,0.7103675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001046195,"about_ca_system_score_gemma":0.0003345292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003293618,"about_ca_topic_score_gemma":0.0001303344,"domain_scores_codex":[0.9960209,0.0001828879,0.0006033523,0.001561303,0.00101982,0.000611771],"domain_scores_gemma":[0.9927832,0.000118452,0.0004220743,0.006097207,0.0001018974,0.0004771486],"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":[0.000006658215,0.00005799468,0.000001387846,0.00007036563,0.0001578415,0.0005665109,0.00001461836,0.000004563461,0.000005762157,0.0004328626,0.9979131,0.0007683569],"study_design_scores_gemma":[0.0002925599,0.00005153682,0.000009128964,0.00004368149,0.0001804304,0.00003088473,0.000006625084,0.0009031642,0.00001762884,0.00007888958,0.9977582,0.000627304],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[1.423338e-7,0.000001514839,0.01433799,0.00007465661,0.001021832,0.0002153717,0.9837981,0.000263653,0.0002867044],"genre_scores_gemma":[9.70204e-7,0.0002402858,0.008757137,0.003105825,0.0004291275,0.00002480897,0.9871617,0.00002509541,0.0002550672],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7013645,"threshold_uncertainty_score":0.9996696,"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."}}