{"id":"W3043958695","doi":"10.1109/access.2020.3011123","title":"NeedFull – a Tweet Analysis Platform to Study Human Needs During the COVID-19 Pandemic in New York State","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada; University of Ottawa","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Computer science; Visualization; Scalability; State (computer science); Data science; Data visualization; Data collection; 2019-20 coronavirus outbreak; World Wide Web; Computer security; Database; Artificial intelligence; Sociology; Virology","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":[0.0008381471,0.0006428129,0.0003244705,0.001473801,0.0006597573,0.0007968924,0.0005984314,0.0006456354,0.007156816],"category_scores_gemma":[0.002741896,0.0001927432,0.0002851322,0.0006849542,0.0001919692,0.002212864,0.001504672,0.0005973012,0.001657143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005422726,"about_ca_system_score_gemma":0.0006851125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009466633,"about_ca_topic_score_gemma":0.02394408,"domain_scores_codex":[0.9996794,0.00008933608,0.00003064582,0.00008221741,0.00008074084,0.0000375694],"domain_scores_gemma":[0.9986363,0.000659229,0.0001171277,0.0001395327,0.0002358477,0.0002119131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002736774,0.0009113697,0.09318474,0.002595244,0.0003953399,0.001680488,0.01374577,0.00536711,0.0662365,0.008453474,0.4120817,0.3926116],"study_design_scores_gemma":[0.0005310765,0.001606277,0.207288,0.0004630709,0.0002835627,0.0008969529,0.01394459,0.2029259,0.02763672,0.02082542,0.52311,0.0004883881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5647348,0.001814669,0.136125,0.007400367,0.001183784,0.003969515,0.1420962,0.0967218,0.04595386],"genre_scores_gemma":[0.7417378,0.00108761,0.1334161,0.001937261,0.0003623329,0.003240737,0.08114298,0.001711171,0.03536388],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009466633,"threshold_uncertainty_score":0.02394193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1540569218514484,"score_gpt":0.370644716661629,"score_spread":0.2165877948101805,"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."}}