{"id":"W4391462717","doi":"10.1109/lra.2024.3414180","title":"Force Push: Robust Single-Point Pushing With Force Feedback","year":2024,"lang":"en","type":"preprint","venue":"IEEE Robotics and Automation Letters","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Technische Universität München; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Single point; Point (geometry); Haptic technology; Computer science; Physics; Mathematics; Simulation; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001699844,0.0004278995,0.0003610837,0.0002719585,0.0001181278,0.0007125781,0.0001583572,0.0002307225,0.00002081288],"category_scores_gemma":[0.00001322074,0.0004128915,0.00009903491,0.0001432624,0.00004752658,0.0001897963,0.000119454,0.0008939017,0.00005218352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001731578,"about_ca_system_score_gemma":0.00002074781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001130067,"about_ca_topic_score_gemma":0.000022821,"domain_scores_codex":[0.99845,0.00003674879,0.0004357398,0.0004348847,0.000296343,0.0003463275],"domain_scores_gemma":[0.9993254,0.00007158909,0.0001312537,0.0003139144,0.00004477592,0.0001130568],"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":[0.00000298324,0.000006887327,0.00004544685,0.0008991875,0.0001035692,0.00001847978,0.0006374399,0.9896626,0.005153937,0.0002992725,0.002377054,0.00079312],"study_design_scores_gemma":[0.0002226003,0.0000203005,0.0003790236,0.0009033189,0.00009133651,0.00002926832,0.00006166184,0.9966926,0.0004510083,0.0003475228,0.0002683088,0.0005330301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08502542,0.0003511218,0.9038599,0.004891587,0.002343718,0.0004724887,0.000004829604,0.001678935,0.001372015],"genre_scores_gemma":[0.976873,0.00003186656,0.02124032,0.0005477238,0.0004200246,0.00002836142,0.00008519999,0.0001667556,0.0006066942],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8918476,"threshold_uncertainty_score":0.9998323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02152249500196499,"score_gpt":0.209132363070022,"score_spread":0.187609868068057,"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."}}