{"id":"W6939659997","doi":"10.6084/m9.figshare.22622996","title":"Additional file 1 of Development of a patients’ satisfaction analysis system using machine learning and lexicon-based methods","year":2023,"lang":"en","type":"article","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of British Columbia","funders":"","keywords":"Development (topology); Feature (linguistics); Quality (philosophy); Active learning (machine learning); Statistical analysis","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001521914,0.0008290214,0.0008854665,0.002267709,0.0004478383,0.001482907,0.001383843,0.0009169446,0.8498737],"category_scores_gemma":[0.0267271,0.0005049124,0.0006870012,0.002316105,0.0002142895,0.001143247,0.001096077,0.0006942989,0.2376902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000901232,"about_ca_system_score_gemma":0.001356663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004861416,"about_ca_topic_score_gemma":0.01011601,"domain_scores_codex":[0.9993708,0.0001704241,0.0001429189,0.0001326807,0.0001239227,0.00005925537],"domain_scores_gemma":[0.9755814,0.02037167,0.0007107282,0.0009284188,0.001959404,0.0004484471],"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":[0.000439027,0.000141879,0.003157171,0.00184911,0.00004486111,0.0001050565,0.0001256264,0.0006923117,0.0002227957,0.0007934184,0.96298,0.02944883],"study_design_scores_gemma":[0.005009533,0.0005092864,0.04097732,0.002068151,0.0002730406,0.0009091887,0.0008093015,0.01249008,0.00395294,0.01740999,0.9152765,0.0003147543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.0005877581,0.00001776386,0.001577719,0.0001060343,0.00003891476,0.00019302,0.9926379,0.002234317,0.002606676],"genre_scores_gemma":[0.02004843,0.0001167939,0.0215067,0.0006930159,0.0001016721,0.003437291,0.9343355,0.003320683,0.0164399],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8498737,"threshold_uncertainty_score":0.2141369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0372968943665748,"score_gpt":0.2646078779575193,"score_spread":0.2273109835909445,"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."}}