{"id":"W6958730148","doi":"10.6084/m9.figshare.22229713.v2","title":"Can-SWaP_V1","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Watershed; Surface water; Water resources; Water quality; Water source; Hydrology (agriculture); Water use; Work (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005883003,0.002473056,0.001455395,0.003946471,0.001583974,0.002307714,0.003492105,0.001846447,0.02926882],"category_scores_gemma":[0.003534408,0.0007507438,0.001252111,0.007908627,0.0007293431,0.0008685916,0.001682066,0.00184914,0.0406772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006789952,"about_ca_system_score_gemma":0.01287583,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7668905,"about_ca_topic_score_gemma":0.8803525,"domain_scores_codex":[0.9992464,0.00006121356,0.00005657604,0.0002080517,0.0002323011,0.0001955602],"domain_scores_gemma":[0.9982672,0.0002218069,0.0001028983,0.0003016607,0.0008781655,0.000228296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004958401,0.0000204282,0.001538079,0.0003671571,0.00003593768,0.00003039378,0.00003334941,0.0005906028,0.0001125526,0.0004300356,0.9944416,0.00235036],"study_design_scores_gemma":[0.0002255015,0.00001573878,0.01407827,0.0002762096,0.00004804904,0.00008342401,0.0001908209,0.002109543,0.0005953585,0.00093424,0.9813829,0.00006006703],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002425309,0.00004898655,0.00005712385,0.00003391293,0.00001031182,0.00001259667,0.9986597,0.0003977168,0.0005371086],"genre_scores_gemma":[0.0004870046,0.00003232108,0.0002003315,0.00001586001,0.000002137871,0.00002561635,0.9988214,0.00003869537,0.0003765921],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9707312,"threshold_uncertainty_score":0.4689646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0332472362323894,"score_gpt":0.2529462102916842,"score_spread":0.2196989740592948,"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."}}