{"id":"W2600954308","doi":"","title":"The business end of objects: Monitoring object orientation","year":2009,"lang":"en","type":"article","venue":"OhioLink ETD Center (Ohio Library and Information Network)","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Miami","keywords":"Orientation (vector space); Object (grammar); Computer science; Computer vision; Artificial intelligence; Business; Mathematics; Geometry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004083268,0.0001835714,0.0002253942,0.0003261347,0.0001667294,0.0006455449,0.0002820142,0.0005237939,0.001550535],"category_scores_gemma":[0.002521772,0.000195997,0.0001134264,0.0002877723,0.0003531257,0.001052862,0.0004742579,0.0005010917,0.0003535591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002003857,"about_ca_system_score_gemma":0.0001824614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009554497,"about_ca_topic_score_gemma":0.001308823,"domain_scores_codex":[0.9998147,0.00004445239,0.000009810819,0.00005622477,0.00004904324,0.00002591219],"domain_scores_gemma":[0.9992144,0.0002238991,0.0002398367,0.0000941754,0.0001008542,0.0001267761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001758527,0.0003776517,0.06326263,0.0002320801,0.00005853473,0.0002829992,0.001191728,0.000694858,0.7940676,0.00168007,0.0005860388,0.1358074],"study_design_scores_gemma":[0.0001041561,0.00273345,0.6910151,0.00005567255,0.0001665779,0.001181765,0.00146657,0.008637305,0.2811377,0.007622224,0.005772864,0.0001066044],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808778,0.0003663717,0.01403091,0.0001150935,0.00002525476,0.00003667845,0.00009516987,0.00006304579,0.004389742],"genre_scores_gemma":[0.9864094,0.0003637091,0.01157681,0.0001280291,0.00001379162,0.00003331026,0.0001268035,0.00001831993,0.001329821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001550535,"threshold_uncertainty_score":0.005187035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009281678288577271,"score_gpt":0.194465003906926,"score_spread":0.1851833256183487,"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."}}