{"id":"W2019484001","doi":"10.1016/j.cviu.2006.01.003","title":"Form representions and means for landmarks: A survey and comparative study","year":2006,"lang":"en","type":"article","venue":"Computer Vision and Image Understanding","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of Alberta","funders":"","keywords":"Landmark; Computer science; Object (grammar); Representation (politics); Artificial intelligence; Principal (computer security); Set (abstract data type); Ideal (ethics); Subject (documents); Pattern recognition (psychology); Computer vision; Information retrieval; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005650615,0.0001423753,0.0002118549,0.000136037,0.0004085873,0.0006817195,0.0001470612,0.00003622948,0.000001433068],"category_scores_gemma":[0.00001460157,0.0001165181,0.00002871009,0.0001984016,0.0001169762,0.0006138339,0.0002406334,0.00007346147,5.380209e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003828249,"about_ca_system_score_gemma":0.00001240628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005214057,"about_ca_topic_score_gemma":0.00005024037,"domain_scores_codex":[0.9989354,0.0001011832,0.0002240725,0.0004337606,0.000132089,0.0001734886],"domain_scores_gemma":[0.999204,0.0003424528,0.00008056565,0.0002099605,0.00009285668,0.00007017089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004010276,0.001989726,0.05566737,0.000353772,0.0002577805,0.00004980197,0.01194238,0.000005460009,0.006945853,0.7936224,0.04171697,0.08704745],"study_design_scores_gemma":[0.003426493,0.00156302,0.1530522,0.000102677,0.00003293525,0.00006760385,0.001934588,0.7578367,0.0008861381,0.07854838,0.001870276,0.0006789816],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01215036,0.0001341047,0.9861848,0.0003625586,0.00006254807,0.0005183251,0.000008736012,0.0001249444,0.0004536151],"genre_scores_gemma":[0.9313913,0.00003947636,0.06831596,0.00005244281,0.00003447972,0.00001349996,0.00001012752,0.000005645372,0.000137054],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.919241,"threshold_uncertainty_score":0.6573837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1097274613269708,"score_gpt":0.3429214515337391,"score_spread":0.2331939902067683,"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."}}