{"id":"W2040747612","doi":"10.1017/s0890060411000230","title":"Considering multiscale scenes to elucidate problems encumbering three-dimensional intellection and navigation","year":2011,"lang":"en","type":"article","venue":"Artificial intelligence for engineering design analysis and manufacturing","topic":"Spatial Cognition and Navigation","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Autodesk (Canada)","funders":"","keywords":"Computer science; Focus (optics); Context (archaeology); Representation (politics); Human–computer interaction; Virtual machine; Data science","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":[0.001006484,0.0005244561,0.0003750925,0.0006906817,0.001259377,0.004302612,0.0008699736,0.001373936,0.002412487],"category_scores_gemma":[0.003921207,0.0003900911,0.0006525036,0.0005019904,0.007539648,0.005460199,0.003566711,0.001140355,0.0001754895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009910577,"about_ca_system_score_gemma":0.0008102912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003474029,"about_ca_topic_score_gemma":0.003422878,"domain_scores_codex":[0.9992323,0.0004230281,0.00003193293,0.0001041966,0.0001242774,0.00008426696],"domain_scores_gemma":[0.9981223,0.001122695,0.0002380078,0.0002486114,0.0001434754,0.0001248879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003951873,0.00003120566,0.001727245,0.0001205623,0.00002278257,0.0004533484,0.007599941,0.04511093,0.004915333,0.9236952,0.0007382611,0.01554569],"study_design_scores_gemma":[0.00001840149,0.00008540589,0.001741413,0.00007847576,0.00003216274,0.0003183829,0.00611499,0.2290365,0.002770576,0.7424611,0.01728889,0.00005388928],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1659309,0.0006882566,0.8051869,0.00299607,0.00007317142,0.00005037408,0.00004370866,0.0002414893,0.02478918],"genre_scores_gemma":[0.895235,0.0003141103,0.1029376,0.0001235373,0.00001597673,0.00005110535,0.00002409476,0.00003631748,0.001262155],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004302612,"threshold_uncertainty_score":0.008070588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0574752531943917,"score_gpt":0.2426983480686937,"score_spread":0.185223094874302,"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."}}