{"id":"W7027482533","doi":"","title":"Depolymerization of chitosan","year":2000,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"","field":"","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Depolymerization; Chitosan; Hydrolysis; Polymer; Yield (engineering)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"other","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002973067,0.001020875,0.0003082831,0.0009523514,0.000390119,0.0002229478,0.0005502978,0.0003196406,0.01365215],"category_scores_gemma":[0.0002298516,0.0002458809,0.0004467734,0.0009522394,0.0001950795,0.0002242675,0.000226334,0.0009204263,0.003465231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008840493,"about_ca_system_score_gemma":0.001185481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02217449,"about_ca_topic_score_gemma":0.03282815,"domain_scores_codex":[0.9996905,0.00001660709,0.00002014528,0.00007727749,0.0001018055,0.0000937245],"domain_scores_gemma":[0.9998567,0.00002970926,0.00001822942,0.00001517414,0.00005345832,0.00002659066],"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":[0.0001047118,0.0000565144,0.00005385693,0.0001552836,0.00001308319,0.0001051387,0.00003115366,0.0001404468,0.9915883,0.0003953107,0.001214573,0.006141625],"study_design_scores_gemma":[0.00002597049,0.0001944123,0.001268594,0.0000179573,0.00002588333,0.00007115612,0.00001270394,0.0004946623,0.9829402,0.0000239643,0.0149118,0.00001264258],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7065844,0.008877647,0.04572433,0.0007107678,0.001066398,0.001877789,0.004960525,0.001718647,0.2284796],"genre_scores_gemma":[0.768328,0.006114852,0.0200822,0.0002852224,0.00007837456,0.0003595483,0.009180881,0.0002688151,0.1953022],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02217449,"threshold_uncertainty_score":0.04567099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00196395425578029,"score_gpt":0.1297146984063663,"score_spread":0.127750744150586,"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."}}