{"id":"W1845267493","doi":"10.1007/978-3-642-14600-8_44","title":"Modelling English Spatial Preposition Detectors","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Categorization, perception, and language","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Detector; Artificial intelligence; Computer vision; Image (mathematics); Algorithm; Telecommunications","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":[0.0006869723,0.000691301,0.001188055,0.0005866734,0.000448852,0.002469594,0.001822239,0.00158688,0.008601491],"category_scores_gemma":[0.003518073,0.001257895,0.001188368,0.0009304131,0.0006820295,0.003250435,0.0009613127,0.001073252,0.001128011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001381009,"about_ca_system_score_gemma":0.0007394743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01872891,"about_ca_topic_score_gemma":0.02392313,"domain_scores_codex":[0.9998043,0.00004850633,0.00001126125,0.00006581095,0.00003202919,0.00003813214],"domain_scores_gemma":[0.9986546,0.001014377,0.00005888286,0.00007640362,0.0001483841,0.00004728615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00024137,0.0000747678,0.001845194,0.0001716717,0.00007786233,0.0003824205,0.0002744651,0.7944243,0.005016548,0.1501569,0.003591696,0.04374282],"study_design_scores_gemma":[0.000007042206,0.000006761884,0.00009321087,0.000005485731,0.000007300353,0.00003045799,0.00001681247,0.9780573,0.0005125701,0.02083826,0.0004196356,0.000005097658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1709398,0.001361201,0.8070277,0.0008449067,0.0001484539,0.00005534868,0.0010579,0.001741514,0.01682322],"genre_scores_gemma":[0.8794985,0.0006948463,0.0999605,0.0001151227,0.0000605069,0.00007603972,0.0009535513,0.0004077808,0.01823319],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01872891,"threshold_uncertainty_score":0.03723979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01373140817010194,"score_gpt":0.2549376811786855,"score_spread":0.2412062730085835,"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."}}