{"id":"W2071049913","doi":"10.3390/informatics1010032","title":"Using Collaborative Tagging for Text Classification: From Text Classification to Opinion Mining","year":2013,"lang":"en","type":"article","venue":"Informatics","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Polytechnique Montréal","funders":"Génome Québec; Genome Canada","keywords":"Ranking (information retrieval); Computer science; Task (project management); Context (archaeology); Information retrieval; Document classification; Natural language processing; Artificial intelligence; World Wide Web; Engineering; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006249466,0.00188318,0.001803649,0.007568046,0.001364307,0.004553067,0.002479907,0.002271348,0.00246487],"category_scores_gemma":[0.01956059,0.0005057178,0.001638733,0.005832557,0.0009334632,0.005722648,0.002149644,0.002370628,0.004402699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001023664,"about_ca_system_score_gemma":0.001055526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002320821,"about_ca_topic_score_gemma":0.003110581,"domain_scores_codex":[0.9937991,0.002621033,0.0005609248,0.001215105,0.001459484,0.0003443564],"domain_scores_gemma":[0.9838849,0.009603442,0.001505558,0.001548716,0.002976781,0.0004806535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002233316,0.0006022223,0.007998455,0.0005924674,0.0002238629,0.0002769006,0.001470157,0.004828481,0.01808324,0.003846802,0.01435805,0.9474961],"study_design_scores_gemma":[0.0001447746,0.0005865489,0.01567755,0.0005214504,0.0005079003,0.0009184303,0.003267175,0.7906516,0.0545004,0.08509315,0.0477982,0.0003328215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02970009,0.001269413,0.9547403,0.001215216,0.0004697577,0.0007134723,0.001111725,0.004134496,0.006645544],"genre_scores_gemma":[0.2364402,0.000949974,0.7534782,0.0004994478,0.0009447619,0.0007312197,0.003020974,0.000299947,0.003635309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007568046,"threshold_uncertainty_score":0.03305078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07513631016913433,"score_gpt":0.3480759311327196,"score_spread":0.2729396209635853,"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."}}