{"id":"W4405788218","doi":"10.1109/iros58592.2024.10802173","title":"Working Backwards: Learning to Place by Picking","year":2024,"lang":"en","type":"article","venue":"","topic":"Engineering Education and Pedagogy","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Artificial intelligence; Human–computer interaction","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":[0.00008429385,0.00009178273,0.00006684379,0.00009434266,0.00002506193,0.0001038315,0.00006688444,0.0000394565,0.0006624645],"category_scores_gemma":[0.00001736809,0.00009473377,0.00002446697,0.0002195253,0.00000277691,0.00005164238,0.00001217813,0.0001949831,0.0006599475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000590016,"about_ca_system_score_gemma":0.00001166472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008814742,"about_ca_topic_score_gemma":0.000007133407,"domain_scores_codex":[0.9995332,0.000005692711,0.00009234623,0.0001166714,0.00007139206,0.0001807051],"domain_scores_gemma":[0.9997706,0.00006326084,0.000002056209,0.00007689049,0.000006182211,0.00008101938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001016958,0.000005614194,0.0004325679,0.0001403982,0.00004886429,0.000005698347,0.003888487,0.5432259,0.01016131,0.001822172,0.3925645,0.04770346],"study_design_scores_gemma":[0.00002151011,0.000006202599,0.00004564636,0.00007436926,0.000002953592,0.000003801191,0.0002111008,0.06301306,0.001296706,0.000004940299,0.9351854,0.0001343287],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1831355,0.008705701,0.3911726,0.00188667,0.01147955,0.0002822538,0.00000309737,0.01158908,0.3917456],"genre_scores_gemma":[0.9714637,0.00004724033,0.001739805,0.0001172209,0.0002098617,0.00001253958,0.000006544944,0.00004858086,0.02635455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7883282,"threshold_uncertainty_score":0.8482509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01151600127393729,"score_gpt":0.2539108105956707,"score_spread":0.2423948093217334,"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."}}