{"id":"W6999802123","doi":"","title":"Développement d'un système collaboratif de tennis de table basé sur un bras robotique de bureau intégrant l'intelligence artificielle","year":2025,"lang":"fr","type":"other","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut de Valorisation des Données","keywords":"Context (archaeology); Dispose pattern; Reel","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":[0.0006755798,0.0008973107,0.0009310303,0.0007072661,0.0008382258,0.001280592,0.00144922,0.001516076,0.01397509],"category_scores_gemma":[0.001266819,0.0005470943,0.0007289848,0.0003902577,0.000483216,0.001170862,0.0008967115,0.0006219853,0.003811639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005476288,"about_ca_system_score_gemma":0.001333446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007517202,"about_ca_topic_score_gemma":0.00482572,"domain_scores_codex":[0.999486,0.0000480277,0.00002950178,0.0001587603,0.0002104898,0.00006718907],"domain_scores_gemma":[0.9993956,0.0001347838,0.00003789032,0.00009293277,0.0002281366,0.0001105745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008308053,0.0004420606,0.006122494,0.000676027,0.0001189828,0.003551356,0.002861362,0.03090111,0.5121916,0.00424981,0.008067462,0.4299869],"study_design_scores_gemma":[0.0002565425,0.003164614,0.01818865,0.000246402,0.0002994352,0.00337261,0.001582895,0.435671,0.370613,0.002025867,0.1643015,0.0002774346],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2750683,0.0007743294,0.6876152,0.0007234702,0.0005991274,0.0007682497,0.0003742174,0.0110359,0.02304119],"genre_scores_gemma":[0.6748037,0.0004769932,0.2719563,0.0002395164,0.00005365421,0.0004876899,0.0008219921,0.0004183636,0.05074187],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01397509,"threshold_uncertainty_score":0.04675132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01300927094488536,"score_gpt":0.2478245817316067,"score_spread":0.2348153107867213,"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."}}