{"id":"W4398557349","doi":"10.7910/dvn/dnw5rw/vio63a","title":"map_question_validation.xml","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; XML; Information retrieval; Database; World Wide Web","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":[],"category_scores_codex":[0.002500303,0.004204675,0.001728081,0.004858824,0.001602059,0.004248807,0.00438838,0.00407487,0.1238036],"category_scores_gemma":[0.01346088,0.001271018,0.002067944,0.005082332,0.001099058,0.003310177,0.004020788,0.002250087,0.16766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002455149,"about_ca_system_score_gemma":0.00380536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02115585,"about_ca_topic_score_gemma":0.02862336,"domain_scores_codex":[0.9972242,0.0005296658,0.0003440641,0.0009152299,0.0005963741,0.0003904115],"domain_scores_gemma":[0.9939015,0.001950726,0.0003728579,0.002119582,0.00133744,0.0003178792],"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":[0.00006786185,0.00002482233,0.0006346367,0.0006457042,0.00002470488,0.00001963211,0.00003174973,0.0002832914,0.0001491857,0.0006348691,0.9956403,0.001843204],"study_design_scores_gemma":[0.0002930695,0.00002305731,0.002304107,0.0003267747,0.00002337458,0.00007320237,0.0001174105,0.00110342,0.001294602,0.002803891,0.9915888,0.00004842323],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001830382,0.00005862439,0.0002162886,0.0001133389,0.00004092872,0.00002140151,0.9957152,0.002491736,0.001159511],"genre_scores_gemma":[0.0006393968,0.00004270455,0.0004748386,0.00009097376,0.000008819797,0.000091692,0.9973846,0.0004585046,0.0008084216],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8761964,"threshold_uncertainty_score":0.4141644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0257288027554626,"score_gpt":0.2740371604337164,"score_spread":0.2483083576782538,"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."}}