{"id":"W7151315608","doi":"10.1109/icosec67334.2025.11459658","title":"Design of Camouflage Military Robot using Raspberry Pi and Machine Learning","year":2025,"lang":"","type":"article","venue":"","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Camouflage; Robot; Raspberry pi; Robotics; Machine vision; Drone","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":[0.0001588796,0.0005606522,0.0004465018,0.0002832715,0.0003235953,0.0003427331,0.001283665,0.0007737402,0.004558722],"category_scores_gemma":[0.0001914078,0.0002755588,0.0003555086,0.00009277132,0.0002118239,0.000319954,0.0003076662,0.0003104527,0.00137966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003597492,"about_ca_system_score_gemma":0.0005839833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003842717,"about_ca_topic_score_gemma":0.003706777,"domain_scores_codex":[0.9998463,0.0000112003,0.00000651293,0.00004235109,0.00006311974,0.00003041053],"domain_scores_gemma":[0.9999108,0.000009130632,0.00001644607,0.00001048971,0.00004032494,0.00001279321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004647927,0.0003261196,0.004808744,0.001076204,0.0001799046,0.001459215,0.00025983,0.2596805,0.2601552,0.008120485,0.0121679,0.4513012],"study_design_scores_gemma":[0.00007112922,0.0009353901,0.00270178,0.00006152134,0.00006962445,0.0005922951,0.00006013714,0.9269421,0.04786735,0.0009561779,0.01968563,0.0000568809],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07555471,0.0007875327,0.8855686,0.0005611604,0.000438477,0.0005585383,0.0001574482,0.006047322,0.03032622],"genre_scores_gemma":[0.8461716,0.0002879292,0.1385853,0.0002384781,0.00003293717,0.00039999,0.0001102545,0.00006805574,0.01410542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004558722,"threshold_uncertainty_score":0.01525038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035685153568422,"score_gpt":0.22461709774681,"score_spread":0.2042602462111258,"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."}}