{"id":"W4393650548","doi":"10.5281/zenodo.2573264","title":"3D IQ Test Task (3D-IQTT) - A Dataset for Quantitative Evaluation of 3D Reconstruction from 2D Images","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Image Processing and 3D Reconstruction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"European Commission","keywords":"Task (project management); Test (biology); Artificial intelligence; Pattern recognition (psychology); Computer science; 3D reconstruction; Computer vision; Geology; Paleontology; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00212202,0.004952984,0.001836673,0.003109354,0.001216996,0.002649666,0.004360767,0.003902198,0.04695532],"category_scores_gemma":[0.009106797,0.0006956905,0.002757713,0.002622301,0.001002715,0.002350454,0.004598954,0.002567964,0.04831554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001765266,"about_ca_system_score_gemma":0.001695778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01299121,"about_ca_topic_score_gemma":0.02776267,"domain_scores_codex":[0.9960917,0.0008531238,0.0003750916,0.0008410015,0.00150588,0.0003331492],"domain_scores_gemma":[0.995591,0.001181897,0.0002332684,0.00139861,0.001218237,0.000376975],"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":[0.0008021396,0.0004507072,0.003049913,0.002189401,0.0001811383,0.0003116245,0.0001609129,0.004780355,0.003599692,0.001545773,0.8999407,0.08298767],"study_design_scores_gemma":[0.0009899123,0.001054912,0.03081415,0.001460861,0.0002079327,0.002504306,0.001168746,0.05353431,0.02226295,0.00856371,0.877031,0.0004072507],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02276827,0.002550357,0.01948781,0.0007740123,0.0008858383,0.001588397,0.8934383,0.03121847,0.02728854],"genre_scores_gemma":[0.01677274,0.0002653672,0.01784281,0.0002578233,0.00006309651,0.000640675,0.9578609,0.001119724,0.005176855],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04695532,"threshold_uncertainty_score":0.1570812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06462840664928166,"score_gpt":0.3056498850064925,"score_spread":0.2410214783572108,"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."}}