{"id":"W4241265541","doi":"10.7287/peerj.preprints.742","title":"Low cost audiovisual playback and recording triggered by radio frequency identification using Raspberry Pi","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Animal Vocal Communication and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Raspberry pi; Transponder (aeronautics); Computer science; Radio-frequency identification; Telemetry; Identification (biology); Set (abstract data type); Real-time computing; Begging; Computer hardware; Speech recognition; Embedded system; Engineering; Telecommunications; Ecology; Biology; Operating system","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":[0.0004112096,0.0006087701,0.0003532853,0.0004223774,0.0002006405,0.0003762247,0.0009897,0.0003461256,0.00453448],"category_scores_gemma":[0.0007266045,0.0002736585,0.0002206041,0.0001943267,0.0003406748,0.0004810801,0.0004709162,0.0003417346,0.001607033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001516995,"about_ca_system_score_gemma":0.00016854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005008032,"about_ca_topic_score_gemma":0.0007014722,"domain_scores_codex":[0.9997122,0.00003514678,0.00001783969,0.00009985133,0.0001046553,0.00003034949],"domain_scores_gemma":[0.9994853,0.0002369598,0.000063068,0.0001062517,0.00006663214,0.00004191938],"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":[0.0003294686,0.00009908871,0.0011336,0.0001528322,0.00001527704,0.0001882013,0.00008507332,0.0002086746,0.9472062,0.000151855,0.0005843324,0.04984536],"study_design_scores_gemma":[0.00009458044,0.001467995,0.02273015,0.0000330467,0.00006849349,0.001149552,0.00008151648,0.009369605,0.9516694,0.0003194344,0.01296042,0.00005572869],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5408069,0.0006881927,0.4392815,0.0001429869,0.0001767761,0.00110776,0.001635955,0.01026159,0.005898295],"genre_scores_gemma":[0.6175321,0.0006137717,0.363507,0.0001933075,0.00009933642,0.00189899,0.001509047,0.0007137483,0.01393276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00453448,"threshold_uncertainty_score":0.01516938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03945890600090191,"score_gpt":0.3244842682216945,"score_spread":0.2850253622207926,"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."}}