{"id":"W2146582625","doi":"10.1145/1182807.1182829","title":"Datalink streaming in wireless sensor networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fondation de l'Association des radiologistes du Québec; National Science Foundation","keywords":"Computer science; Real-time computing; Byte; Computer network; Network packet; Wireless sensor network; Bit error rate; Wireless; Testbed; Retransmission; Channel (broadcasting); Bandwidth (computing); Error detection and correction; Frame (networking); Forward error correction; Decoding methods; Computer hardware; Telecommunications; Algorithm","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":[],"consensus_categories":[],"category_scores_codex":[0.0002318568,0.0001963072,0.0002080988,0.0001557788,0.00007852604,0.0001754081,0.0008655663,0.0001240877,0.00001435043],"category_scores_gemma":[0.000006053649,0.0001852733,0.00005055779,0.0008157766,0.00004575553,0.0003649841,0.0003035505,0.0002264621,0.0000276017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006052866,"about_ca_system_score_gemma":0.00002120309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007452298,"about_ca_topic_score_gemma":0.000765458,"domain_scores_codex":[0.9981548,0.00008057788,0.0003618133,0.0005617789,0.0002626817,0.0005784172],"domain_scores_gemma":[0.9988723,0.0001637644,0.00008024013,0.0007767286,0.00003903846,0.00006797451],"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":[0.000002306277,0.00009456118,0.005592578,0.000003043637,0.000003418818,0.0001006346,0.00001849943,0.8877692,0.0003906439,0.09531917,0.001080152,0.009625807],"study_design_scores_gemma":[0.00029427,0.00001307067,0.004720719,0.00002709817,0.000001538978,0.00001470828,0.0000115345,0.992428,0.001103698,0.0001189048,0.001013117,0.0002533517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1648486,0.00008204899,0.8199072,0.0002291228,0.0005675807,0.00009920942,7.460685e-7,0.0003713648,0.01389413],"genre_scores_gemma":[0.9598926,0.00001324016,0.03798898,0.0001919742,0.0002290438,0.000006677602,0.00002163557,0.00001760266,0.001638241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7950441,"threshold_uncertainty_score":0.7555227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006778567195630783,"score_gpt":0.2038790911725375,"score_spread":0.1971005239769067,"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."}}