{"id":"W4394166883","doi":"10.6084/m9.figshare.20290155","title":"LLSM Dataset for Virtual and Augmented reality","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Augmented reality; Virtual reality; Computer science; 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":[],"consensus_categories":[],"category_scores_codex":[0.001261922,0.004354813,0.00245174,0.003617042,0.001217959,0.002717979,0.004557225,0.002959007,0.05987246],"category_scores_gemma":[0.00400024,0.0007542655,0.002865813,0.004053316,0.0005732775,0.001720529,0.00415577,0.002428436,0.09611162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001386103,"about_ca_system_score_gemma":0.001972828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.021003,"about_ca_topic_score_gemma":0.04005881,"domain_scores_codex":[0.9975405,0.0003621653,0.000257703,0.0006388326,0.0008884013,0.000312464],"domain_scores_gemma":[0.9984139,0.0002413051,0.00009483691,0.0005622959,0.0005588999,0.0001286697],"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":[0.0001412252,0.00008170316,0.0006371228,0.000814833,0.00008905239,0.000104413,0.00003945538,0.00170384,0.001067799,0.0007156458,0.9755648,0.01904011],"study_design_scores_gemma":[0.0001829366,0.00008600107,0.004199544,0.0004483248,0.00008482672,0.0004233448,0.00026084,0.008310451,0.003078332,0.003049308,0.979745,0.000131163],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001056084,0.0005964919,0.002928554,0.0002375305,0.0002023884,0.0001475265,0.9859137,0.005917436,0.0030004],"genre_scores_gemma":[0.002047966,0.0001711286,0.003720063,0.00009061741,0.00001877308,0.0002544436,0.9922213,0.000319263,0.001156422],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05987246,"threshold_uncertainty_score":0.2002933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04785136724868878,"score_gpt":0.2987220307735383,"score_spread":0.2508706635248495,"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."}}