{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001009942,0.0001789659,0.0001860931,0.00009455318,0.0003091849,0.0003008486,0.0008022831,0.0001178495,0.0813311],"category_scores_gemma":[0.0003746963,0.0001794999,0.00004044024,0.0001373032,0.00001019846,0.000313883,0.000787629,0.0002710866,0.00009324351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003659739,"about_ca_system_score_gemma":0.0001976332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002551565,"about_ca_topic_score_gemma":0.00001440878,"domain_scores_codex":[0.9988286,0.00005118962,0.0001818152,0.000539712,0.0001954535,0.0002031506],"domain_scores_gemma":[0.9989353,0.0001189932,0.0001933217,0.0006284355,0.00005431859,0.00006964218],"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":[0.000003599844,0.000014938,2.421658e-8,0.0002916656,0.00001149914,0.000006538839,0.000005873634,0.000001099835,5.474766e-7,0.000002359407,0.9850392,0.0146227],"study_design_scores_gemma":[0.0001929453,0.00006535235,0.000002986178,0.0002139044,0.00001069904,0.00006207932,0.000004720571,0.0004818571,0.00001696161,0.00005462885,0.998684,0.0002097954],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[5.662245e-8,0.0001707525,0.000235763,0.00009412724,0.0003433696,0.0002024561,0.9988916,0.00005292532,0.000008973331],"genre_scores_gemma":[3.60982e-7,0.000008748189,0.0004720238,0.0002634471,0.0001151006,0.0002944762,0.9987618,0.000007397584,0.00007662868],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08123786,"threshold_uncertainty_score":0.9195087,"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."}}