{"id":"W4394278905","doi":"10.6084/m9.figshare.6210125","title":"Raw data VR Acceptance","year":2018,"lang":"en","type":"dataset","venue":"Figshare","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Raw data; Computer science; Virtual reality; Computer graphics (images); Human–computer interaction","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002658252,0.001154562,0.0009528138,0.005168545,0.0007504678,0.003009881,0.00156685,0.000797088,0.437851],"category_scores_gemma":[0.03642468,0.0004122684,0.001199695,0.00521973,0.0002734697,0.002030103,0.001897626,0.001732338,0.1803751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008902682,"about_ca_system_score_gemma":0.001540578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006889814,"about_ca_topic_score_gemma":0.006319339,"domain_scores_codex":[0.9967129,0.0004196425,0.0004910945,0.0005099148,0.001536543,0.0003299204],"domain_scores_gemma":[0.9711428,0.01302241,0.001992038,0.003440195,0.009710508,0.0006920704],"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":[0.0006700508,0.0002649285,0.02385357,0.001181975,0.0001008422,0.0001041361,0.0004591746,0.0004432475,0.0004493982,0.002125179,0.8585539,0.1117937],"study_design_scores_gemma":[0.0002051447,0.0002471232,0.08014839,0.0007028664,0.00008502683,0.0002599901,0.001057675,0.0005528337,0.0008934265,0.002339261,0.9134116,0.00009683792],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004663096,0.0001112584,0.0008976993,0.0001919923,0.0001720089,0.0002726836,0.9744445,0.001576013,0.01767072],"genre_scores_gemma":[0.02493771,0.0002319827,0.0030387,0.0003563099,0.0001771157,0.002465067,0.9396614,0.001598671,0.02753308],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.437851,"threshold_uncertainty_score":0.8018373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1525054655764877,"score_gpt":0.3584132030218343,"score_spread":0.2059077374453465,"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."}}