{"id":"W2048480914","doi":"10.1037/a0016273","title":"Use of self-to-object and object-to-object spatial relations in locomotion.","year":2009,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Spatial Cognition and Navigation","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Object (grammar); Representation (politics); Consistency (knowledge bases); Object-based spatial database; Artificial intelligence; Computer vision; Computer science; Spatial relation; Method; Object relations theory; Psychology; Mathematics; Spatial analysis; Object-oriented programming; Spatial database","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":[0.0006237464,0.0002815287,0.0001868289,0.0001792727,0.0001171748,0.0003861689,0.0002203251,0.0003210308,0.0008105117],"category_scores_gemma":[0.003460584,0.0001727881,0.0001481642,0.00007951066,0.0005241725,0.0004857352,0.0004211084,0.0002626367,0.00009267583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00015531,"about_ca_system_score_gemma":0.0001751988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000452074,"about_ca_topic_score_gemma":0.00111198,"domain_scores_codex":[0.9997435,0.00006709834,0.00002862802,0.00008644981,0.00005146925,0.00002288364],"domain_scores_gemma":[0.9981192,0.0006521097,0.0004786169,0.0004149127,0.0002030582,0.000132132],"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":[0.001514924,0.0006617426,0.05915289,0.0004183018,0.0001133591,0.0001131468,0.002101435,0.001086875,0.8378178,0.0004294647,0.0001707701,0.09641924],"study_design_scores_gemma":[0.0001812593,0.007487287,0.734874,0.00007290042,0.0002072776,0.0006492823,0.001206453,0.005369983,0.2447759,0.001871448,0.003208359,0.00009581382],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974697,0.00009018452,0.001944189,0.00001498665,0.000004034469,0.00001401674,0.00001780163,0.00001925813,0.0004259351],"genre_scores_gemma":[0.993944,0.00007983379,0.005502213,0.00001540292,9.549279e-7,0.00001869094,0.00004289609,0.000005743063,0.000390336],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008105117,"threshold_uncertainty_score":0.003298759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02090434229319563,"score_gpt":0.293355559444915,"score_spread":0.2724512171517194,"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."}}