{"id":"W2131542563","doi":"10.1142/s0218348x05002805","title":"TOWARD A QUANTIFICATION OF SELF-SIMILARITY IN PLANTS","year":2005,"lang":"en","type":"article","venue":"Fractals","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Branching (polymer chemistry); Self-similarity; Similarity (geometry); lilac; Formalism (music); Oryza sativa; Computer science; Theoretical computer science; Mathematics; Data mining; Artificial intelligence; Botany; Biology; Chemistry; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.002453903,0.0005519907,0.0005786968,0.004102214,0.0006238263,0.002785074,0.001125986,0.001125447,0.0005882266],"category_scores_gemma":[0.009876618,0.0003376992,0.0005577275,0.0017542,0.004030996,0.004416122,0.002232525,0.001184798,0.0001553883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001320573,"about_ca_system_score_gemma":0.0004898347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004321515,"about_ca_topic_score_gemma":0.0003536555,"domain_scores_codex":[0.9986269,0.0004411336,0.0001254992,0.0002609053,0.0004636912,0.00008182563],"domain_scores_gemma":[0.9940327,0.003073166,0.0009961892,0.0007630177,0.0008232438,0.0003117688],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00005755031,0.00006322184,0.005067218,0.0001737864,0.0000692247,0.00008394854,0.000582755,0.07768048,0.01664263,0.8458341,0.0005907413,0.05315426],"study_design_scores_gemma":[0.00001152951,0.00008415485,0.002572992,0.00005465198,0.00001775407,0.0002050927,0.0002124855,0.3035892,0.005513153,0.6840137,0.003680702,0.00004460794],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1376304,0.000830738,0.8579313,0.000239364,0.00002746714,0.00003905178,0.00008195684,0.0002254006,0.002994444],"genre_scores_gemma":[0.6691055,0.0004592972,0.3293636,0.00006510437,0.00005947764,0.00006997527,0.0001531519,0.00006884397,0.0006550899],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004102214,"threshold_uncertainty_score":0.01297766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03337363633261478,"score_gpt":0.2409677274406615,"score_spread":0.2075940911080467,"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."}}