{"id":"W2330123567","doi":"10.2514/6.2005-7129","title":"New Cloud Micro Sensors for the Aerosonde UAV","year":2005,"lang":"en","type":"article","venue":"Infotech@Aerospace","topic":"Atmospheric aerosols and clouds","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Aerosan","funders":"","keywords":"Cloud computing; Computer science; 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":[0.0006163186,0.0005107676,0.0004924562,0.000761002,0.0005079703,0.0009092626,0.0007307241,0.0007431145,0.003115818],"category_scores_gemma":[0.0007203711,0.0004372869,0.0002799231,0.0004843714,0.000205161,0.001517999,0.0007002275,0.001090033,0.0005758462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009126224,"about_ca_system_score_gemma":0.0006288481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00493602,"about_ca_topic_score_gemma":0.02580501,"domain_scores_codex":[0.9992781,0.00005753406,0.00002124714,0.0001374597,0.0004337421,0.00007197632],"domain_scores_gemma":[0.9992934,0.00010404,0.00006186077,0.00007707078,0.0003443912,0.0001191978],"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":[0.001100422,0.000223744,0.03630569,0.000291805,0.0001200721,0.0002307643,0.0003267351,0.004590297,0.5545655,0.005738044,0.02842494,0.3680821],"study_design_scores_gemma":[0.0002949704,0.002187012,0.1091797,0.0001733117,0.0003578446,0.001564686,0.0004476557,0.2505361,0.3661769,0.004468311,0.2643283,0.0002852567],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5015628,0.02283134,0.3921796,0.007145265,0.00296011,0.0007106928,0.005012058,0.007783773,0.05981436],"genre_scores_gemma":[0.687224,0.002313752,0.2801512,0.001455543,0.0006381312,0.0001866446,0.003051638,0.0003192608,0.02465995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00493602,"threshold_uncertainty_score":0.01042348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008109204557189073,"score_gpt":0.2242875311657394,"score_spread":0.2161783266085503,"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."}}