{"id":"W4409644693","doi":"10.1016/j.dib.2025.111569","title":"Experimental datasets on the extraction of functional ingredients from seaweeds for controlling bacterial infection","year":2025,"lang":"en","type":"article","venue":"Data in Brief","topic":"Seaweed-derived Bioactive Compounds","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Eesti Teadusagentuur; Canadian Poultry Research Council","keywords":"Extraction (chemistry); Research article; Computational biology; Chemistry; Computer science; Chromatography; Biology","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":[0.001358312,0.0007743085,0.0008101892,0.001212262,0.0006629748,0.0006267548,0.0006063738,0.0007561867,0.005189868],"category_scores_gemma":[0.001887149,0.0001942521,0.001014199,0.001747095,0.0003492005,0.0005134374,0.0005155629,0.0005413229,0.001861874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004639897,"about_ca_system_score_gemma":0.0007436239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003404861,"about_ca_topic_score_gemma":0.00564661,"domain_scores_codex":[0.9989041,0.0001302885,0.0001921485,0.0002655756,0.0004109583,0.00009688636],"domain_scores_gemma":[0.9985858,0.0004962499,0.0002269103,0.0002024877,0.0004371204,0.00005142789],"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":[0.009622647,0.004136438,0.1204434,0.01636334,0.001530019,0.001488275,0.0003166084,0.05453441,0.5035996,0.002860822,0.04017331,0.2449311],"study_design_scores_gemma":[0.0004126736,0.006110209,0.2340363,0.0009251391,0.00167555,0.001289403,0.0007844746,0.04108629,0.5301913,0.004041738,0.1790079,0.000439036],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.6662064,0.005883451,0.0223115,0.0004484997,0.0002099235,0.001187179,0.2903852,0.001043079,0.01232483],"genre_scores_gemma":[0.5366495,0.007793067,0.04461568,0.0004305879,0.00006857092,0.002614116,0.4023358,0.0002194234,0.005273328],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.005189868,"threshold_uncertainty_score":0.01736182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07548292926273968,"score_gpt":0.3055815663320391,"score_spread":0.2300986370692994,"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."}}